Recent advances in convolutional neural networks

•We give an overview of the basic components of CNN.•We discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss function, regularization, optimization and fast computation.•We introduce the applications of CNN on various tasks, including image classifica...

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Published in	Pattern recognition Vol. 77; pp. 354 - 377
Main Authors	Gu, Jiuxiang, Wang, Zhenhua, Kuen, Jason, Ma, Lianyang, Shahroudy, Amir, Shuai, Bing, Liu, Ting, Wang, Xingxing, Wang, Gang, Cai, Jianfei, Chen, Tsuhan
Format	Journal Article
Language	English
Published	Elsevier Ltd 01.05.2018
Subjects	Convolutional neural network Deep learning Deep learning Convolutional neural network
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Abstract	•We give an overview of the basic components of CNN.•We discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss function, regularization, optimization and fast computation.•We introduce the applications of CNN on various tasks, including image classification, object detection, object tracking, pose estimation, text detection, visual saliency detection, action recognition, scene labeling, speech and natural language processing.•We discuss the challenges in CNN and give several future research directions. In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing. Among different types of deep neural networks, convolutional neural networks have been most extensively studied. Leveraging on the rapid growth in the amount of the annotated data and the great improvements in the strengths of graphics processor units, the research on convolutional neural networks has been emerged swiftly and achieved state-of-the-art results on various tasks. In this paper, we provide a broad survey of the recent advances in convolutional neural networks. We detailize the improvements of CNN on different aspects, including layer design, activation function, loss function, regularization, optimization and fast computation. Besides, we also introduce various applications of convolutional neural networks in computer vision, speech and natural language processing.
AbstractList	•We give an overview of the basic components of CNN.•We discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss function, regularization, optimization and fast computation.•We introduce the applications of CNN on various tasks, including image classification, object detection, object tracking, pose estimation, text detection, visual saliency detection, action recognition, scene labeling, speech and natural language processing.•We discuss the challenges in CNN and give several future research directions. In the last few years, deep learning has led to very good performance on a variety of problems, such as visual recognition, speech recognition and natural language processing. Among different types of deep neural networks, convolutional neural networks have been most extensively studied. Leveraging on the rapid growth in the amount of the annotated data and the great improvements in the strengths of graphics processor units, the research on convolutional neural networks has been emerged swiftly and achieved state-of-the-art results on various tasks. In this paper, we provide a broad survey of the recent advances in convolutional neural networks. We detailize the improvements of CNN on different aspects, including layer design, activation function, loss function, regularization, optimization and fast computation. Besides, we also introduce various applications of convolutional neural networks in computer vision, speech and natural language processing.
Author	Wang, Xingxing Kuen, Jason Chen, Tsuhan Gu, Jiuxiang Shuai, Bing Shahroudy, Amir Wang, Zhenhua Wang, Gang Ma, Lianyang Cai, Jianfei Liu, Ting
Author_xml	– sequence: 1 givenname: Jiuxiang orcidid: 0000-0002-3437-5084 surname: Gu fullname: Gu, Jiuxiang email: jgu004@ntu.edu.sg organization: ROSE Lab, Interdisciplinary Graduate School, Nanyang Technological University, Singapore – sequence: 2 givenname: Zhenhua surname: Wang fullname: Wang, Zhenhua organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 3 givenname: Jason surname: Kuen fullname: Kuen, Jason email: jasonkuen@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 4 givenname: Lianyang surname: Ma fullname: Ma, Lianyang email: lyma@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 5 givenname: Amir surname: Shahroudy fullname: Shahroudy, Amir email: amir3@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 6 givenname: Bing surname: Shuai fullname: Shuai, Bing email: bshuai001@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 7 givenname: Ting surname: Liu fullname: Liu, Ting email: LIUT0016@e.ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 8 givenname: Xingxing surname: Wang fullname: Wang, Xingxing email: wangxx@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 9 givenname: Gang surname: Wang fullname: Wang, Gang email: WangGang@ntu.edu.sg organization: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore – sequence: 10 givenname: Jianfei surname: Cai fullname: Cai, Jianfei email: asjfcai@ntu.edu.sg organization: School of Computer Science and Engineering, Nanyang Technological University, Singapore – sequence: 11 givenname: Tsuhan surname: Chen fullname: Chen, Tsuhan email: tsuhan@ntu.edu.sg organization: School of Computer Science and Engineering, Nanyang Technological University, Singapore
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Cites_doi	10.1109/TPAMI.2015.2389824 10.1016/S0031-3203(96)00044-1 10.1016/S0031-3203(01)00178-9 10.1137/090752286 10.1016/j.patcog.2016.06.013 10.1007/s11263-015-0822-0 10.1016/j.patcog.2015.08.027 10.1016/j.patcog.2015.02.003 10.1016/j.patcog.2011.05.017 10.1109/TPAMI.2012.231 10.1016/j.patcog.2016.07.001 10.1109/TPAMI.2016.2577031 10.1016/j.patcog.2012.03.004 10.1016/j.patcog.2015.04.018 10.1016/j.patcog.2012.10.006 10.1109/TNN.2010.2066286 10.1016/j.patcog.2017.06.006 10.1016/j.patcog.2011.09.021 10.1109/TPAMI.2012.59 10.1109/TIP.2016.2605305 10.1109/18.532878 10.1016/j.patrec.2017.08.001 10.1016/j.patcog.2017.06.009 10.1016/j.patcog.2003.10.012 10.3390/s101211259 10.1016/j.patcog.2015.11.019 10.1016/j.patcog.2012.09.015 10.1016/j.patcog.2012.07.013 10.1080/09548980701418942 10.1007/s11263-015-0823-z 10.1016/j.patcog.2017.06.002 10.1109/TPAMI.2016.2572683 10.1016/S0031-3203(01)00129-7 10.1016/j.patcog.2016.05.019 10.1016/j.patrec.2017.04.004 10.1007/s00365-006-0663-2 10.1016/j.patcog.2014.08.013 10.1113/jphysiol.1968.sp008455 10.1038/381607a0 10.1162/neco.1997.9.8.1735 10.1109/78.134406 10.1109/TPAMI.2015.2439281 10.1016/0893-6080(88)90469-8 10.1016/S0893-6080(98)00116-6 10.1016/j.patcog.2015.04.019 10.1109/MSP.2012.2211477 10.1016/j.asoc.2015.06.048 10.1016/j.patcog.2017.01.032 10.1109/MSP.2012.2205597 10.1016/j.patcog.2016.03.023 10.1016/j.patcog.2016.01.027 10.1016/j.patrec.2015.10.013 10.1109/LSP.2015.2441781 10.1016/j.patcog.2014.04.018 10.1109/29.21701 10.1109/5.726791 10.1109/LSP.2017.2657381 10.1109/TPAMI.2009.167 10.1016/j.patcog.2016.12.005 10.1364/AO.29.004790 10.1109/TIP.2016.2531289 10.1049/ip-vis:19941301 10.1016/j.patcog.2016.09.022 10.1109/TPAMI.2011.235 10.1109/TPAMI.2013.122 10.1162/089976600300015015 10.1016/j.patcog.2015.04.005 10.1109/TMI.2003.815867 10.1016/j.patcog.2016.10.023 10.1016/j.patcog.2010.09.020 10.1016/j.patcog.2014.11.006 10.1142/S0218001493000339 10.1016/j.patcog.2017.04.027 10.1016/j.patcog.2016.07.026 10.1016/0031-3203(81)90028-5 10.1109/TPAMI.2016.2599174
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References	Szegedy, Vanhoucke, Ioffe, Shlens, Wojna (bib0041) 2016 Ng, Zeng, Zhang, Yeung, Pedrycz (bib0079) 2016; 60 X. Chen, A.L. Yuille, Articulated pose estimation by a graphical model with image dependent pairwise relations, in: Proceedings of the Advances in Neural Information Processing Systems (NIPS), 2014, pp. 1736–1744. Xu, Huang, Zhang, Tao (bib0100) 2015 Moczulski, Denil, Appleyard, de Freitas (bib0145) 2016 Pluim, Maintz, Viergever (bib0187) 2003; 22 Patacchiola, Cangelosi (bib0220) 2017; 71 Delakis, Garcia (bib0235) 2008 Zhang (bib0061) 2004 Choromanska, Henaff, Mathieu, Arous, LeCun (bib0101) 2015 Xu, Su (bib0236) 2015 Kümmerer, Theis, Bethge (bib0252) 2015 Han, Mao, Dally (bib0146) 2016 Sercu, Goel (bib0294) 2016 Cao, Liu, Yang, Yu, Wang, Wang, Huang, Wang, Huang, Xu (bib0031) 2015 Qian (bib0108) 1999; 12 Gidaris, Komodakis (bib0205) 2015 Gers, Schmidhuber, Cummins (bib0242) 2000; 12 Wang, Lu, Li, Jiang, Liu (bib0306) 2015 Lin, Maire, Belongie, Hays, Perona, Ramanan, Dollár, Zitnick (bib0199) 2014 Presti, La Cascia (bib0255) 2016; 53 Paine, Jin, Yang, Lin, Huang (bib0115) 2011 Vig, Dorr, Cox (bib0251) 2014 Tang, Lee, Suen (bib0229) 1996; 29 Sercu, Goel (bib0040) 2016 Deng (bib0062) 2012; 29 Zuo, Wang, Shuai, Zhao, Yang (bib0170) 2015; 48 Yu, Xiong, Droppo, Stolcke, Ye, Li, Zweig (bib0297) 2016 Chen, Raitio, Valentini-Botinhao, Yamagishi, Ling (bib0299) 2014 J. Gu, C. Jianfei, G. Wang, T. Chen, Stack-captioning: coarse-to-fine learning for image captioning, volume abs/1709.03376, 2017. Farabet, Couprie, Najman, LeCun (bib0276) 2013; 35 Everingham, Eslami, Van Gool, Williams, Winn, Zisserman (bib0172) 2015; 111 Ji, Xu, Yang, Yu (bib0265) 2013; 35 Abdel-Hamid, Mohamed, Jiang, Penn (bib0289) 2012 Shi, Bai, Yao (bib0243) 2015 Lin, Shen, Lu, Jia (bib0186) 2015 Jaderberg, Simonyan, Vedaldi, Zisserman (bib0240) 2015 Rippel, Snoek, Adams (bib0048) 2015 Weinberger, Dasgupta, Langford, Smola, Attenberg (bib0164) 2009 Z. Yan, V. Jagadeesh, D. DeCoste, W. Di, R. Piramuthu, Hd-cnn: hierarchical deep convolutional neural network for image classification, in: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2740–2748. Yu, Wang, Chen, Wei (bib0046) 2014 Yao, Yu, Seide, Su, Deng, Gong (bib0288) 2012 Zhang, Lee, Lee, EDU (bib0033) 2016 Prechelt (bib0118) 2012 volume abs/1412.6115, 2014. Goodfellow, Ibarz, Arnoud, Shet (bib0239) 2014 Bai, Shi, Zhang, Cai, Qi (bib0233) 2017; 66 Dong, Loy, He, Tang (bib0036) 2016; 38 Le, Sarlós, Smola (bib0141) 2013; 85 Szegedy, Liu, Jia, Sermanet, Reed, Anguelov, Erhan, Vanhoucke, Rabinovich (bib0010) 2015 Tang (bib0019) 2013 Das, Agrawal, Zitnick, Parikh, Batra (bib0035) 2016 Zhang, Itoh, Tanida, Ichioka (bib0006) 1990; 29 Paulin, Revaud, Harchaoui, Perronnin, Schmid (bib0097) 2014 He, Zhang, Ren, Sun (bib0056) 2015 Hauberg, Freifeld, Larsen, Fisher III, Hansen (bib0098) 2016 Liu, Lin, Shen (bib0273) 2015; 48 Liu, Wang, Foroosh, Tappen, Pensky (bib0165) 2015 Zeiler, Krishnan, Taylor, Fergus (bib0026) 2010 Sutskever, Martens, Dahl, Hinton (bib0103) 2013 Gomez, Nicolaou, Karatzas (bib0234) 2017; 67 El Ayadi, Kamel, Karray (bib0284) 2011; 44 Kim, Smaragdis (bib0147) 2016 Liu, Han, Zhang, Wen, Liu (bib0249) 2015 Fan, Xu, Wu, Gong (bib0216) 2010; 21 Sullivan (bib0151) 1996; 42 Chen, Yuille (bib0226) 2015 Clevert, Unterthiner, Hochreiter (bib0058) 2016 Liu, Luo, Qiu, Wang, Tang (bib0072) 2016 Xiao, Zhang, Yang, Peng, Zhang (bib0176) 2014 Pedersoli, Vedaldi, Gonzalez, Roca (bib0195) 2015; 48 Li, Wang, Tian, Ding (bib0194) 2015; 48 Denton, Chintala, Fergus (bib0086) 2015 Cheng, Yu, Feris, Kumar, Choudhary, Chang (bib0144) 2015 Lu, Javidi, Lazebnik (bib0212) 2016 Yu, Hermann, Blunsom, Pulman (bib0310) 2014 Yang, Luo, Loy, Tang (bib0180) 2015 Hadsell, Chopra, LeCun (bib0066) 2006 Zeiler, Fergus (bib0011) 2014 Mariet, Sra (bib0161) 2015 Yu, Koltun (bib0037) 2016 Li, Li, Porikli (bib0217) 2014 Nogueira, Penatti, dos Santos (bib0169) 2017; 61 Reed, Akata, Yan, Logeswaran, Schiele, Lee (bib0085) 2016 Li, Yu (bib0248) 2015 LeCun, Bottou, Orr, Müller (bib0013) 2012 Gkioxari, Girshick, Malik (bib0262) 2015 Yin, Schütze (bib0313) 2015 Ren, He, Girshick, Sun (bib0204) 2017; 39 Mirza, Osindero (bib0077) 2014 Saxe, McClelland, Ganguli (bib0105) 2014 Huang, Siniscalchi, Lee (bib0301) 2017 Chen, Guan, Wang (bib0153) 2010; 10 Doersch, Gupta, Efros (bib0106) 2015 Xu, Wang, Chen, Li (bib0057) 2015 Lin, Chen, Yan (bib0018) 2014 Nair, Hinton (bib0014) 2010 Peng, Zhang, Zhang (bib0275) 2013; 46 Gong, Wang, Guo, Lazebnik (bib0052) 2014 Zhou, Lu, Li, Tian (bib0154) 2012 Zhang, Wei, Wu, Cai, Lu, Nguyen, Do (bib0190) 2016; 25 Guo, Lai (bib0254) 2014; 47 Tóth (bib0295) 2014 Wijnhoven, de With (bib0021) 2010 Guo, Yao, Chen (bib0157) 2016 Tousch, Herbin, Audibert (bib0173) 2012; 45 Kingma, Ba (bib0109) 2015 Palaz, Collobert, Doss (bib0291) 2013 Zinkevich, Weimer, Li, Smola (bib0022) 2010 Jégou, Perronnin, Douze, Sanchez, Perez, Schmid (bib0053) 2012; 34 Salimans, Goodfellow, Zaremba, Cheung, Radford, Chen (bib0087) 2016 Mishkin, Matas (bib0102) 2016 Ngiam, Chen, Chia, Koh, Le, Ng (bib0023) 2010 Wang, Wang, Wang (bib0175) 2015 Gkioxari, Girshick, Malik (bib0259) 2015 Liu, Anguelov, Erhan, Szegedy, Reed (bib0211) 2016 Waibel, Hanazawa, Hinton, Shikano, Lang (bib0298) 1989; 37 Tompson, Jain, LeCun, Bregler (bib0224) 2014 D. Amodei, R. Anubhai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, J. Chen, M. Chrzanowski, A. Coates, G. Diamos, et al., Deep speech 2: End-to-end speech recognition in english and mandarin, 2016, pp. 173–182. Wang, Manning (bib0090) 2013 Oseledets (bib0140) 2011; 33 Abdel-Hamid, Mohamed, Jiang, Deng, Penn, Yu (bib0290) 2014 Hecht-Nielsen (bib0005) 1988; 1 J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, T. Darrell, Decaf: a deep convolutional activation feature for generic visual recognition, 2014. Minervini, Fischbach, Scharr, Tsaftaris (bib0181) 2016; 81 Xiao, Xu, Yang, Zhang, Peng, Zhang (bib0191) 2015 He, Zhang, Ren, Sun (bib0203) 2015; 37 Dean, Corrado, Monga, Chen, Devin, Mao, Senior, Tucker, Yang, Le (bib0114) 2012 Girshick, Iandola, Darrell, Malik (bib0197) 2015 Collobert, Weston, Bottou, Karlen, Kavukcuoglu, Kuksa (bib0314) 2011; 12 Wan, Zeiler, Zhang, Cun, Fergus (bib0045) 2013 H. Hu, R. Peng, Y.-W. Tai, C.-K. Tang, Network trimming: a data-driven neuron pruning approach towards efficient deep architectures, volume abs/1607.03250, 2016. Shuai, Wang, Zuo, Wang, Zhao (bib0279) 2015 Fukushima, Miyake (bib0002) 1982 Han, Pool, Tran, Dally (bib0156) 2015 Hinton, Srivastava, Krizhevsky, Sutskever, Salakhutdinov (bib0017) 2012 Felzenszwalb, Girshick, McAllester, Ramanan (bib0207) 2010; 32 Zhou, Zheng, Zhu, Latecki (bib0272) 2016; 59 Zeiler, Ranzato, Monga, Mao, Yang, Le, Nguyen, Senior, Vanhoucke, Dean (bib0055) 2013 Wen, Wu, Wang, Chen, Li (bib0166) 2016 M. Jaderberg, K. Simonyan, A. Vedaldi, A. Zisserman, Reading text in the wild with convolutional neural networks, volume 116, 2016, pp. 1–20. Ding, Lin, Wang, Chao (bib0071) 2015; 48 Shen, Gan, Zeng (bib0124) 2016 Simonyan, Zisserman (bib0268) 2014 Denil, Shakibi, Dinh, de Freitas (bib0136) 2013 Zagoruyko, Komodakis (bib0125) 2016 Hyvärinen, Köster (bib0043) 2007; 18 Eslami, Heess, Weber, Tassa, Kavukcuoglu, Hinton (bib0083) 2016 Sohn, Lee, Yan (bib0084) 2015 Goodfellow, Warde-Farley, Mirza, Courville, Bengio (bib0059) 2013 Jung, Kim, Jain (bib0231) 2004; 37 Niu, Suen (bib0007) 2012; 45 Shuai, Zuo, Wang, Wang (bib0281) 2016 Zhang, Yao, Shi, Bai (bib0238) 2015 Uria, Murray, Renals, Valentini-Botinhao, Bridle (bib0300) 2015 Xie, Yang, Wang, Lin (bib0099) 2015 Zhang, Song (bib0213) 2013; 46 Visin, Kastner, Courville, Bengio, Matteucci, Cho (bib0029) 2015 Y. Gong, L. Liu, M. Yang, L. Bourdev, Compressing deep convolutional networks using vector quantization, in: arXiv preprint Huang, Qiao, Tang (bib0237) 2014 Endres, Hoiem (bib0200) 2014; 36 Shi, Petterson, Dror, Langford, Smola, Vishwanathan (bib0163) 2009; 10 Krause, Gebru, Deng, Li, Fei-Fei (bib0188) 2014 Srivastava, Greff, Schmidhuber (bib0122) 2015 Lin, RoyChowdhury, Maji (bib0192) 2015 Hong, You, Kwak, Han (bib0219) 2015 Vaillant, Monrocq, Le Cun (bib0198) 1994; 141 S. Chetlur, C. Woolley, P. Vandermersch, J. Cohen, J. Tran, B. Catanzaro, E. Shelhamer, Cudnn: efficient primitives for deep learningabs/1410.0759 (2014). Wang, Oates (bib0024) 2015 Loshchilov, Hutter (bib0110) 2017 Zhang, Yao, Sun, Lu (bib0214) 2013; 46 Nowlan, Platt (bib0196) 1994 Kingma, Welling (bib0073) 2014 Pinheiro, Collobert (bib0278) 2014 Hinton, Deng, Yu, Dahl, Mohamed, Jaitly, Senior, Vanhoucke, Nguyen, Sainath (bib0286) 2012; 29 Sainath, Kingsbury, Mohamed, Dahl, Saon, Soltau, Beran, Aravkin, Ramabhadran (bib0296) 2013 Yang, Patras (bib0093) 2015 Mostajabi, Yadollahpour, Shakhnarovich (bib0282) 2015 Xue, Li, Gong (bib0135) 2013 Krause, Jin, Yang, Fei-Fei (bib0189) 2015 Pratt (bib0155) 1988 Chen, Wilson, Tyree, Weinberger, Chen (bib0162) 2015 Long, Shelhamer, Darrell (bib0028) 2017; 39 Recht, Re, Wright, Niu (bib0113) 2011 Le Cun, Denker, Henderson, Howard, Hubbard, Jackel (bib0003) 1989 Zheng, Liu, Chen, Ge, Zhao (bib0025) 2014 Vasilache, Johnson, Mathieu, Chintala, Piantino, LeCun (bib0131) 2015 Kalchbrenner, Grefenstette, Blunsom (bib0311) 2014 Oquab, Bottou, Laptev, Sivic (bib0258) 2014 Collobert, Weston (bib0309) 2008 Shrivastava, Gupta, Girshick (bib0209) 2016 Olshausen (bib0081) 1996; 381 LeCun, Bottou, Bengio, Haffner (bib0004) 1998; 86 Dasgupta, Kumar, Sarlós (bib0142) 2011 Kim, Jernite, Sontag, Rush (bib0304) 2016 Wang, Ge, Li, Fang (bib0264) 2017; 92 Zhang, Bengio, Hardt, Recht, Vinyals (bib0119) 2017 Chéron, Laptev, Schmid (bib0269) 2015 Courbariaux, Bengio (bib0150) 2016 Jaderberg, Vedaldi, Zisserman (bib0244) 2014 Zhou, Wu, Ni, Zhou, Wen, Zou (bib0149) 2016 Wang, Wu, Coates, Ng (bib0015) 2012 Hoshen, Weiss, Wilson (bib0292) 2015 Tompson, Goroshin, Jain, LeCun, Bregler (bib0092) 2015 Simo-Serra, Trulls, Ferraz, Kokkinos, Moreno-Noguer (bib0208) 2014 Rastegari, Ordonez, Redmon, Farhadi (bib0148) 2016 Nishi, Miura (bib0221) 2017 Zhao, Ouyang, Li, Wang (bib0247) 2015 Glorot, Bengio (bib0104) 2010 Jozefowicz, Vinyals, Schuster, Shazeer, Wu (bib0303) 2016 Im, Ahn, Memisevic, Bengio (b Zhuang (10.1016/j.patcog.2017.10.013_bib0116) 2013 Dasgupta (10.1016/j.patcog.2017.10.013_bib0142) 2011 10.1016/j.patcog.2017.10.013_bib0245 Zhang (10.1016/j.patcog.2017.10.013_bib0190) 2016; 25 Endres (10.1016/j.patcog.2017.10.013_bib0200) 2014; 36 Vaillant (10.1016/j.patcog.2017.10.013_bib0198) 1994; 141 Zhang (10.1016/j.patcog.2017.10.013_bib0213) 2013; 46 Yu (10.1016/j.patcog.2017.10.013_bib0310) 2014 Saxe (10.1016/j.patcog.2017.10.013_bib0105) 2014 Srinivas (10.1016/j.patcog.2017.10.013_bib0160) 2015 Tang (10.1016/j.patcog.2017.10.013_bib0019) 2013 Boureau (10.1016/j.patcog.2017.10.013_bib0016) 2010 Lin (10.1016/j.patcog.2017.10.013_bib0199) 2014 Sainath (10.1016/j.patcog.2017.10.013_bib0296) 2013 Lu (10.1016/j.patcog.2017.10.013_bib0212) 2016 Chen (10.1016/j.patcog.2017.10.013_bib0283) 2015 Lin (10.1016/j.patcog.2017.10.013_bib0068) 2017 Lin (10.1016/j.patcog.2017.10.013_bib0186) 2015 Chéron (10.1016/j.patcog.2017.10.013_bib0269) 2015 Liu (10.1016/j.patcog.2017.10.013_bib0072) 2016 Zeiler (10.1016/j.patcog.2017.10.013_bib0027) 2011 Xu (10.1016/j.patcog.2017.10.013_bib0057) 2015 Zeiler (10.1016/j.patcog.2017.10.013_bib0047) 2013 Nogueira (10.1016/j.patcog.2017.10.013_bib0169) 2017; 61 Xie (10.1016/j.patcog.2017.10.013_bib0094) 2015 Chen (10.1016/j.patcog.2017.10.013_bib0218) 2016; 38 Sohn (10.1016/j.patcog.2017.10.013_bib0084) 2015 Tikhonov (10.1016/j.patcog.2017.10.013_bib0089) 1943; 39 He (10.1016/j.patcog.2017.10.013_bib0050) 2015; 37 Tóth (10.1016/j.patcog.2017.10.013_bib0295) 2014 Yao (10.1016/j.patcog.2017.10.013_bib0288) 2012 Kim (10.1016/j.patcog.2017.10.013_bib0304) 2016 Yang (10.1016/j.patcog.2017.10.013_bib0093) 2015 Le Cun (10.1016/j.patcog.2017.10.013_bib0003) 1989 Huang (10.1016/j.patcog.2017.10.013_bib0129) 2016 Lee (10.1016/j.patcog.2017.10.013_bib0082) 2006 Jung (10.1016/j.patcog.2017.10.013_bib0231) 2004; 37 Jaderberg (10.1016/j.patcog.2017.10.013_bib0240) 2015 Kümmerer (10.1016/j.patcog.2017.10.013_bib0252) 2015 Moczulski (10.1016/j.patcog.2017.10.013_bib0145) 2016 He (10.1016/j.patcog.2017.10.013_bib0241) 2016 Guo (10.1016/j.patcog.2017.10.013_bib0254) 2014; 47 Das (10.1016/j.patcog.2017.10.013_bib0035) 2016 Denton (10.1016/j.patcog.2017.10.013_bib0086) 2015 Vinciarelli (10.1016/j.patcog.2017.10.013_bib0230) 2002; 35 He (10.1016/j.patcog.2017.10.013_bib0123) 2016 Nowlan (10.1016/j.patcog.2017.10.013_bib0196) 1994 Wan (10.1016/j.patcog.2017.10.013_bib0045) 2013 Singh (10.1016/j.patcog.2017.10.013_bib0126) 2016 Springenberg (10.1016/j.patcog.2017.10.013_bib0060) 2013 Chopra (10.1016/j.patcog.2017.10.013_bib0065) 2005 Zhang (10.1016/j.patcog.2017.10.013_bib0119) 2017 Egmont-Petersen (10.1016/j.patcog.2017.10.013_bib0168) 2002; 35 Long (10.1016/j.patcog.2017.10.013_bib0028) 2017; 39 Madjarov (10.1016/j.patcog.2017.10.013_bib0020) 2012; 45 LeCun (10.1016/j.patcog.2017.10.013_bib0004) 1998; 86 Zeiler (10.1016/j.patcog.2017.10.013_bib0026) 2010 Xie (10.1016/j.patcog.2017.10.013_bib0099) 2015 Courbariaux (10.1016/j.patcog.2017.10.013_bib0150) 2016 Zheng (10.1016/j.patcog.2017.10.013_bib0025) 2014 Srivastava (10.1016/j.patcog.2017.10.013_bib0122) 2015 Tran (10.1016/j.patcog.2017.10.013_bib0266) 2015 Shi (10.1016/j.patcog.2017.10.013_bib0163) 2009; 10 Gers (10.1016/j.patcog.2017.10.013_bib0242) 2000; 12 Hinton (10.1016/j.patcog.2017.10.013_bib0286) 2012; 29 10.1016/j.patcog.2017.10.013_bib0132 Mathieu (10.1016/j.patcog.2017.10.013_bib0049) 2014 10.1016/j.patcog.2017.10.013_bib0130 10.1016/j.patcog.2017.10.013_bib0257 Schaul (10.1016/j.patcog.2017.10.013_bib0111) 2013 Ngiam (10.1016/j.patcog.2017.10.013_bib0023) 2010 Jain (10.1016/j.patcog.2017.10.013_bib0223) 2014 Vincent (10.1016/j.patcog.2017.10.013_bib0078) 2008 Zhang (10.1016/j.patcog.2017.10.013_bib0214) 2013; 46 El Ayadi (10.1016/j.patcog.2017.10.013_bib0284) 2011; 44 Fukushima (10.1016/j.patcog.2017.10.013_bib0002) 1982 Uijlings (10.1016/j.patcog.2017.10.013_bib0185) 2013; 104 Zeiler (10.1016/j.patcog.2017.10.013_bib0055) 2013 Salamon (10.1016/j.patcog.2017.10.013_bib0095) 2017; 24 Patacchiola (10.1016/j.patcog.2017.10.013_bib0220) 2017; 71 Oseledets (10.1016/j.patcog.2017.10.013_bib0140) 2011; 33 Cheng (10.1016/j.patcog.2017.10.013_bib0144) 2015 Khosla (10.1016/j.patcog.2017.10.013_bib0179) 2011; 2 Donahue (10.1016/j.patcog.2017.10.013_bib0270) 2017; 39 Oquab (10.1016/j.patcog.2017.10.013_bib0258) 2014 Gkioxari (10.1016/j.patcog.2017.10.013_bib0261) 2015 Szegedy (10.1016/j.patcog.2017.10.013_bib0042) 2017 Shaham (10.1016/j.patcog.2017.10.013_bib0067) 2017 Zuo (10.1016/j.patcog.2017.10.013_bib0170) 2015; 48 Zhang (10.1016/j.patcog.2017.10.013_bib0112) 2015 Presti (10.1016/j.patcog.2017.10.013_bib0255) 2016; 53 Zhou (10.1016/j.patcog.2017.10.013_bib0034) 2016 Pan (10.1016/j.patcog.2017.10.013_bib0253) 2015 Liu (10.1016/j.patcog.2017.10.013_bib0273) 2015; 48 Chen (10.1016/j.patcog.2017.10.013_bib0153) 2010; 10 Doersch (10.1016/j.patcog.2017.10.013_bib0106) 2015 LeCun (10.1016/j.patcog.2017.10.013_bib0013) 2012 Yu (10.1016/j.patcog.2017.10.013_bib0143) 2014 Eslami (10.1016/j.patcog.2017.10.013_bib0083) 2016 Zhang (10.1016/j.patcog.2017.10.013_bib0263) 2016; 25 Nishi (10.1016/j.patcog.2017.10.013_bib0221) 2017 Yin (10.1016/j.patcog.2017.10.013_bib0313) 2015 Szegedy (10.1016/j.patcog.2017.10.013_bib0041) 2016 Wijnhoven (10.1016/j.patcog.2017.10.013_bib0021) 2010 Prechelt (10.1016/j.patcog.2017.10.013_bib0118) 2012 Wang (10.1016/j.patcog.2017.10.013_bib0246) 2015 Sercu (10.1016/j.patcog.2017.10.013_bib0294) 2016 Zagoruyko (10.1016/j.patcog.2017.10.013_bib0125) 2016 He (10.1016/j.patcog.2017.10.013_bib0250) 2015; 115 Krause (10.1016/j.patcog.2017.10.013_bib0188) 2014 Conneau (10.1016/j.patcog.2017.10.013_bib0315) 2016 Deng (10.1016/j.patcog.2017.10.013_bib0287) 2013 Waibel (10.1016/j.patcog.2017.10.013_bib0298) 1989; 37 10.1016/j.patcog.2017.10.013_bib0280 Han (10.1016/j.patcog.2017.10.013_bib0146) 2016 Kingma (10.1016/j.patcog.2017.10.013_bib0109) 2015 10.1016/j.patcog.2017.10.013_bib0152 Yann N. Dauphin (10.1016/j.patcog.2017.10.013_bib0308) 2017 Tousch (10.1016/j.patcog.2017.10.013_bib0173) 2012; 45 Yoo (10.1016/j.patcog.2017.10.013_bib0206) 2015 Zhang (10.1016/j.patcog.2017.10.013_bib0215) 2015; 48 Xu (10.1016/j.patcog.2017.10.013_bib0100) 2015 10.1016/j.patcog.2017.10.013_bib0159 Zhao (10.1016/j.patcog.2017.10.013_bib0247) 2015 Mirza (10.1016/j.patcog.2017.10.013_bib0077) 2014 Zhang (10.1016/j.patcog.2017.10.013_bib0238) 2015 Fan (10.1016/j.patcog.2017.10.013_bib0216) 2010; 21 Loshchilov (10.1016/j.patcog.2017.10.013_bib0110) 2017 Lavin (10.1016/j.patcog.2017.10.013_bib0133) 2016 Xiao (10.1016/j.patcog.2017.10.013_bib0191) 2015 Pedersoli (10.1016/j.patcog.2017.10.013_bib0195) 2015; 48 Gidaris (10.1016/j.patcog.2017.10.013_bib0205) 2015 Dong (10.1016/j.patcog.2017.10.013_bib0036) 2016; 38 Sainath (10.1016/j.patcog.2017.10.013_bib0134) 2013 Sullivan (10.1016/j.patcog.2017.10.013_bib0151) 1996; 42 Jégou (10.1016/j.patcog.2017.10.013_bib0053) 2012; 34 Jaderberg (10.1016/j.patcog.2017.10.013_bib0244) 2014 Deng (10.1016/j.patcog.2017.10.013_bib0285) 1991; 39 Olshausen (10.1016/j.patcog.2017.10.013_bib0081) 1996; 381 Paine (10.1016/j.patcog.2017.10.013_sbref0115) 2011 Branson (10.1016/j.patcog.2017.10.013_bib0183) 2014 Redmon (10.1016/j.patcog.2017.10.013_bib0210) 2016 Liu (10.1016/j.patcog.2017.10.013_bib0070) 2016 Jozefowicz (10.1016/j.patcog.2017.10.013_bib0303) 2016 Farabet (10.1016/j.patcog.2017.10.013_bib0276) 2013; 35 Simonyan (10.1016/j.patcog.2017.10.013_bib0009) 2015 Tang (10.1016/j.patcog.2017.10.013_bib0229) 1996; 29 Noh (10.1016/j.patcog.2017.10.013_bib0030) 2015 Fu (10.1016/j.patcog.2017.10.013_bib0271) 1981; 13 Hadsell (10.1016/j.patcog.2017.10.013_bib0066) 2006 Wen (10.1016/j.patcog.2017.10.013_bib0166) 2016 Pluim (10.1016/j.patcog.2017.10.013_bib0187) 2003; 22 Zhang (10.1016/j.patcog.2017.10.013_bib0256) 2016; 60 Zhang (10.1016/j.patcog.2017.10.013_bib0006) 1990; 29 Cao (10.1016/j.patcog.2017.10.013_bib0031) 2015 10.1016/j.patcog.2017.10.013_bib0177 Wang (10.1016/j.patcog.2017.10.013_bib0306) 2015 Li (10.1016/j.patcog.2017.10.013_bib0194) 2015; 48 Bagherinezhad (10.1016/j.patcog.2017.10.013_bib0167) 2017 Wang (10.1016/j.patcog.2017.10.013_bib0090) 2013 Targ (10.1016/j.patcog.2017.10.013_sbref0127) 2016 Szegedy (10.1016/j.patcog.2017.10.013_bib0010) 2015 Zhang (10.1016/j.patcog.2017.10.013_bib0184) 2014 He (10.1016/j.patcog.2017.10.013_bib0012) 2016 Ioffe (10.1016/j.patcog.2017.10.013_bib0120) 2015 Goodfellow (10.1016/j.patcog.2017.10.013_bib0059) 2013 Liu (10.1016/j.patcog.2017.10.013_bib0211) 2016 Shi (10.1016/j.patcog.2017.10.013_bib0243) 2015 Yu (10.1016/j.patcog.2017.10.013_bib0297) 2016 10.1016/j.patcog.2017.10.013_bib0293 Huang (10.1016/j.patcog.2017.10.013_bib0301) 2017 Sutskever (10.1016/j.patcog.2017.10.013_bib0103) 2013 Rippel (10.1016/j.patcog.2017.10.013_bib0048) 2015 Vasilache (10.1016/j.patcog.2017.10.013_bib0131) 2015 Shen (10.1016/j.patcog.2017.10.013_bib0124) 2016 Abdel-Hamid (10.1016/j.patcog.2017.10.013_bib0290) 2014 Ba (10.1016/j.patcog.2017.10.013_bib0091) 2013 Wang (10.1016/j.patcog.2017.10.013_bib0264) 2017; 92 Shuai (10.1016/j.patcog.2017.10.013_bib0279) 2015 He (10.1016/j.patcog.2017.10.013_bib0203) 2015; 37 Zhou (10.1016/j.patcog.2017.10.013_sbref0147) 2016 Gomez (10.1016/j.patcog.2017.10.013_bib0234) 2017; 67 Zeiler (10.1016/j.patcog.2017.10.013_bib0011) 2014 Bu (10.1016/j.patcog.2017.10.013_bib0274) 2016; 59 Eigen (10.1016/j.patcog.2017.10.013_bib0096) 2015 Hochreiter (10.1016/j.patcog.2017.10.013_bib0121) 1997; 9 Collobert (10.1016/j.patcog.2017.10.013_bib0314) 2011; 12 Eskenazi (10.1016/j.patcog.2017.10.013_bib0232) 2017; 64 Collobert (10.1016/j.patcog.2017.10.013_bib0309) 2008 Huang (10.1016/j.patcog.2017.10.013_bib0237) 2014 Kalchbrenner (10.1016/j.patcog.2017.10.013_bib0311) 2014 Mariet (10.1016/j.patcog.2017.10.013_bib0161) 2015 Lin (10.1016/j.patcog.2017.10.013_bib0018) 2014 Shuai (10.1016/j.patcog.2017.10.013_bib0281) 2016 Yao (10.1016/j.patcog.2017.10.013_bib0117) 2007; 26 Salimans (10.1016/j.patcog.2017.10.013_bib0087) 2016 Guo (10.1016/j.patcog.2017.10.013_bib0157) 2016 Hubel (10.1016/j.patcog.2017.10.013_bib0001) 1968 Fan (10.1016/j.patcog.2017.10.013_bib0227) 2015 Visin (10.1016/j.pat
References_xml	– start-page: 588 year: 2013 end-page: 595 ident: bib0260 article-title: Poselet conditioned pictorial structures publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 886 year: 2015 end-page: 890 ident: bib0238 article-title: Automatic discrimination of text and non-text natural images publication-title: Proceedings of the International Conference on Document Analysis and Recognition (ICDAR) – start-page: 842 year: 2015 end-page: 850 ident: bib0191 article-title: The application of two-level attention models in deep convolutional neural network for fine-grained image classification publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – year: 2016 ident: bib0039 article-title: Wavenet: a generative model for raw audio publication-title: CoRR abs/1609.03499 – volume: 71 start-page: 132 year: 2017 end-page: 143 ident: bib0220 article-title: Head pose estimation in the wild using convolutional neural networks and adaptive gradient methods publication-title: Pattern Recognit. – start-page: 770 year: 2016 end-page: 778 ident: bib0012 article-title: Deep residual learning for image recognition publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 44 start-page: 572 year: 2011 end-page: 587 ident: bib0284 article-title: Survey on speech emotion recognition: features, classification schemes, and databases publication-title: Pattern Recognit. – start-page: 2377 year: 2015 end-page: 2385 ident: bib0122 article-title: Training very deep networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1080 year: 2015 end-page: 1088 ident: bib0261 article-title: Contextual action recognition with rCNN publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 834 year: 2014 end-page: 849 ident: bib0184 article-title: Part-based r-cnns for fine-grained category detection publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – start-page: 1746 year: 2014 end-page: 1751 ident: bib0312 article-title: Convolutional neural networks for sentence classification publication-title: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) – start-page: 646 year: 2016 end-page: 661 ident: bib0316 article-title: Deep networks with stochastic depth publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – year: 2012 ident: bib0017 article-title: Improving neural networks by preventing co-adaptation of feature detectors publication-title: CoRR abs/1207.0580 – start-page: 1725 year: 2014 end-page: 1732 ident: bib0267 article-title: Large-scale video classification with convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 2365 year: 2013 end-page: 2369 ident: bib0135 article-title: Restructuring of deep neural network acoustic models with singular value decomposition publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – start-page: 2650 year: 2015 end-page: 2658 ident: bib0096 article-title: Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 3973 year: 2015 end-page: 3981 ident: bib0180 article-title: A large-scale car dataset for fine-grained categorization and verification publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 26 year: 2014 end-page: 33 ident: bib0188 article-title: Learning features and parts for fine-grained recognition publication-title: Proceedings of the International Conference on Pattern Recognition (ICPR) – start-page: 73 year: 2012 end-page: 86 ident: bib0051 article-title: Unsupervised discovery of mid-level discriminative patches publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – year: 2016 ident: bib0150 article-title: Binarynet: training deep neural networks with weights and activations constrained to+ 1 or-1 publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 3429 year: 2016 end-page: 3433 ident: bib0294 article-title: Advances in very deep convolutional neural networks for LVCSR publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – start-page: 1134 year: 2015 end-page: 1142 ident: bib0205 article-title: Object detection via a multi-region and semantic segmentation-aware cnn model publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 315 year: 2013 end-page: 320 ident: bib0296 article-title: Improvements to deep convolutional neural networks for LVCSR publication-title: Proceedings of the Automatic Speech Recognition and Understanding (ASRU) Workshops – start-page: 1735 year: 2006 end-page: 1742 ident: bib0066 article-title: Dimensionality reduction by learning an invariant mapping publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 580 year: 2014 end-page: 587 ident: bib0202 article-title: Rich feature hierarchies for accurate object detection and semantic segmentation publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 2595 year: 2010 end-page: 2603 ident: bib0022 article-title: Parallelized stochastic gradient descent publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1379 year: 2016 end-page: 1387 ident: bib0157 article-title: Dynamic network surgery for efficient DNNs publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 45 start-page: 3084 year: 2012 end-page: 3104 ident: bib0020 article-title: An extensive experimental comparison of methods for multi-label learning publication-title: Pattern Recognit. – start-page: 2645 year: 2015 end-page: 2654 ident: bib0099 article-title: Hyper-class augmented and regularized deep learning for fine-grained image classification publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 497 year: 2014 end-page: 511 ident: bib0237 article-title: Robust scene text detection with convolution neural network induced mser trees publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – start-page: 3620 year: 2016 end-page: 3629 ident: bib0281 article-title: Dag-recurrent neural networks for scene labeling publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – year: 2014 ident: bib0183 article-title: Improved bird species recognition using pose normalized deep convolutional nets publication-title: Proceedings of the British Machine Vision Conference (BMVC) – volume: 22 start-page: 986 year: 2003 end-page: 1004 ident: bib0187 article-title: Mutual-information-based registration of medical images: a survey publication-title: IEEE Trans. Med. Imaging – start-page: 249 year: 2010 end-page: 256 ident: bib0104 article-title: Understanding the difficulty of training deep feedforward neural networks publication-title: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) – start-page: 901 year: 1994 end-page: 908 ident: bib0196 article-title: A convolutional neural network hand tracker publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 10 start-page: 11259 year: 2010 end-page: 11273 ident: bib0153 article-title: Approximate nearest neighbor search by residual vector quantization publication-title: Sensors – volume: 60 start-page: 875 year: 2016 end-page: 889 ident: bib0079 article-title: Dual autoencoders features for imbalance classification problem publication-title: Pattern Recognit. – volume: 39 start-page: 1137 year: 2017 end-page: 1149 ident: bib0204 article-title: Faster r-CNN: towards real-time object detection with region proposal networks publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – year: 2017 ident: bib0067 article-title: Learning by coincidence: siamese networks and common variable learning publication-title: Pattern Recognit. – start-page: 2094 year: 2013 end-page: 2102 ident: bib0174 article-title: Discriminative transfer learning with tree-based priors publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 740 year: 2014 end-page: 755 ident: bib0199 article-title: Microsoft Coco: Common Objects in Context publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – volume: 70 start-page: 60 year: 2017 end-page: 74 ident: bib0201 article-title: Textproposals: a text-specific selective search algorithm for word spotting in the wild publication-title: Pattern Recognit. – start-page: 37 year: 2015 end-page: 45 ident: bib0107 article-title: Learning to see by moving publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 387 year: 2015 end-page: 394 ident: bib0236 article-title: Robust seed localization and growing with deep convolutional features for scene text detection publication-title: Proceedings of the International Conference on Multimedia Retrieval (ICMR) – start-page: 1279 year: 2010 end-page: 1287 ident: bib0023 article-title: Tiled convolutional neural networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – year: 2017 ident: bib0221 article-title: Generation of human depth images with body part labels for complex human pose recognition publication-title: Pattern Recognit. – start-page: 1078 year: 2014 end-page: 1082 ident: bib0295 article-title: Convolutional deep maxout networks for phone recognition. publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – year: 2011 ident: bib0115 article-title: GPU asynchronous stochastic gradient descent to speed up neural network training publication-title: CoRR – volume: 18 start-page: 81 year: 2007 end-page: 100 ident: bib0043 article-title: Complex cell pooling and the statistics of natural images publication-title: Network – start-page: 82 year: 2014 end-page: 90 ident: bib0278 article-title: Recurrent convolutional neural networks for scene labeling publication-title: Proceedings of the International Conference on Machine Learning (ICML) – reference: D. Amodei, R. Anubhai, E. Battenberg, C. Case, J. Casper, B. Catanzaro, J. Chen, M. Chrzanowski, A. Coates, G. Diamos, et al., Deep speech 2: End-to-end speech recognition in english and mandarin, 2016, pp. 173–182. – year: 2014 ident: bib0217 article-title: Deeptrack: learning discriminative feature representations by convolutional neural networks for visual tracking publication-title: Proceedings of the British Machine Vision Conference (BMVC) – reference: , volume abs/1412.6115, 2014. – start-page: 807 year: 2010 end-page: 814 ident: bib0014 article-title: Rectified linear units improve restricted Boltzmann machines publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 24 start-page: 279 year: 2017 end-page: 283 ident: bib0095 article-title: Deep convolutional neural networks and data augmentation for environmental sound classification publication-title: Signal Process. Lett. (SPL) – start-page: 806 year: 2015 end-page: 814 ident: bib0165 article-title: Sparse convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – year: 2013 ident: bib0277 article-title: Indoor semantic segmentation using depth information publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – reference: J. Gu, C. Jianfei, G. Wang, T. Chen, Stack-captioning: coarse-to-fine learning for image captioning, volume abs/1709.03376, 2017. – start-page: 28 year: 2016 end-page: 36 ident: bib0126 article-title: Swapout: learning an ensemble of deep architectures publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 2921 year: 2016 end-page: 2929 ident: bib0034 article-title: Learning deep features for discriminative localization publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – reference: S. Chetlur, C. Woolley, P. Vandermersch, J. Cohen, J. Tran, B. Catanzaro, E. Shelhamer, Cudnn: efficient primitives for deep learningabs/1410.0759 (2014). – start-page: 215 year: 1968 end-page: 243 ident: bib0001 article-title: Receptive fields and functional architecture of monkey striate cortex publication-title: J. Physiol. – volume: 59 start-page: 188 year: 2016 end-page: 198 ident: bib0274 article-title: Scene parsing using inference embedded deep networks publication-title: Pattern Recognit. – volume: 48 start-page: 3004 year: 2015 end-page: 3015 ident: bib0170 article-title: Exemplar based deep discriminative and shareable feature learning for scene image classification publication-title: Pattern Recognit. – year: 2016 ident: bib0303 article-title: Exploring the limits of language modeling publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – volume: 10 start-page: 2615 year: 2009 end-page: 2637 ident: bib0163 article-title: Hash kernels for structured data publication-title: J. Mach. Learn. Res. (JMLR) – start-page: 3517 year: 2013 end-page: 3521 ident: bib0055 article-title: On rectified linear units for speech processing publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – reference: M. Jaderberg, K. Simonyan, A. Vedaldi, A. Zisserman, Reading text in the wild with convolutional neural networks, volume 116, 2016, pp. 1–20. – start-page: 2285 year: 2015 end-page: 2294 ident: bib0162 article-title: Compressing neural networks with the hashing trick publication-title: Proceedings of the International Conference on Machine Learning (ICML) – year: 2015 ident: bib0131 article-title: Fast convolutional nets with fbfft: aGPU performance evaluation publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 4278 year: 2017 end-page: 4284 ident: bib0042 article-title: Inception-v4, inception-resnet and the impact of residual connections on learning publication-title: Proceedings of the AAAI Conference on Artificial Intelligence – start-page: 512 year: 2014 end-page: 528 ident: bib0244 article-title: Deep features for text spotting publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – volume: 13 start-page: 3 year: 1981 end-page: 16 ident: bib0271 article-title: A survey on image segmentation publication-title: Pattern Recognit. – volume: 30 year: 2013 ident: bib0054 article-title: Rectifier nonlinearities improve neural network acoustic models publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 61 start-page: 539 year: 2017 end-page: 556 ident: bib0169 article-title: Towards better exploiting convolutional neural networks for remote sensing scene classification publication-title: Pattern Recognit. – year: 2015 ident: bib0160 article-title: Data-free parameter pruning for deep neural networks publication-title: Proceedings of the British Machine Vision Conference (BMVC) – start-page: 1113 year: 2009 end-page: 1120 ident: bib0164 article-title: Feature hashing for large scale multitask learning publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 53 start-page: 130 year: 2016 end-page: 147 ident: bib0255 article-title: 3D skeleton-based human action classification: a survey publication-title: Pattern Recognit. – volume: 7 start-page: 669 year: 1993 end-page: 688 ident: bib0064 article-title: Signature verification using a siamese time delay neural network publication-title: Int. J. Pattern Recognit. Artif. Intell. (IJPRAI) – start-page: 4489 year: 2015 end-page: 4497 ident: bib0266 article-title: Learning spatiotemporal features with 3d convolutional networks publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – volume: 35 start-page: 2279 year: 2002 end-page: 2301 ident: bib0168 article-title: Image processing with neural networksa review publication-title: Pattern Recognit. – volume: 9 start-page: 1735 year: 1997 end-page: 1780 ident: bib0121 article-title: Long short-term memory publication-title: Neural Comput. – start-page: 2741 year: 2016 end-page: 2749 ident: bib0304 article-title: Character-aware neural language models publication-title: Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) – volume: 2 start-page: 1 year: 2011 ident: bib0179 article-title: Novel dataset for fine-grained image categorization: stanford dogs publication-title: Proceedings of the IEEE International Conference on Computer Vision (CVPR Workshops – start-page: 612 year: 2016 end-page: 621 ident: bib0033 article-title: Augmenting supervised neural networks with unsupervised objectives for large-scale image classification publication-title: Proceedings of the International Conference on Machine Learning (ICML) – year: 2016 ident: bib0158 article-title: Designing energy-efficient convolutional neural networks using energy-aware pruning publication-title: CoRR abs/1611.05128 – start-page: 118 year: 2013 end-page: 126 ident: bib0090 article-title: Fast dropout training publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 71 start-page: 118 year: 2017 end-page: 131 ident: bib0182 article-title: Lg-cnn: from local parts to global discrimination for fine-grained recognition publication-title: Pattern Recognit. – start-page: 290 year: 2008 end-page: 294 ident: bib0235 article-title: Text detection with convolutional neural networks publication-title: Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP) – volume: 51 start-page: 148 year: 2016 end-page: 175 ident: bib0193 article-title: Human detection from images and videos: a survey publication-title: Pattern Recognit. – start-page: 169 year: 2012 end-page: 178 ident: bib0154 article-title: Scalar quantization for large scale image search publication-title: Proceedings of the 20th ACM International Conference on Multimedia – reference: P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, Y. LeCun, Overfeat: integrated recognition, localization and detection using convolutional networks (2014). – start-page: 2470 year: 2015 end-page: 2478 ident: bib0262 article-title: Actions and attributes from wholes and parts publication-title: Proceedings of the IEEE International Conference on Computer Vision (ICCV) – year: 2015 ident: bib0175 article-title: Learning fine-grained features via a CNN tree for large-scale classification publication-title: CoRR abs/1511.04534 – start-page: 815 year: 2015 end-page: 823 ident: bib0069 article-title: Facenet: a unified embedding for face recognition and clustering publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 4700 year: 2016 end-page: 4708 ident: bib0129 article-title: Densely connected convolutional networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 66 start-page: 437 year: 2017 end-page: 446 ident: bib0233 article-title: Text/non-text image classification in the wild with convolutional neural networks publication-title: Pattern Recognit. – start-page: 3304 year: 2012 end-page: 3308 ident: bib0015 article-title: End-to-end text recognition with convolutional neural networks publication-title: Proceedings of the International Conference on Pattern Recognition (ICPR) – year: 2016 ident: bib0146 article-title: Deep compression: compressing deep neural network with pruning, trained quantization and huffman coding publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 525 year: 2016 end-page: 542 ident: bib0148 article-title: Xnor-net: imagenet classification using binary convolutional neural networks publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – start-page: 249 year: 2013 end-page: 256 ident: bib0116 article-title: A fast parallel SGD for matrix factorization in shared memory systems publication-title: Proceedings of the ACM conference on Recommender systems RecSys – start-page: 2857 year: 2015 end-page: 2865 ident: bib0144 article-title: An exploration of parameter redundancy in deep networks with circulant projections publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – year: 2014 ident: bib0223 article-title: Learning human pose estimation features with convolutional networks publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 3581 year: 2014 end-page: 3589 ident: bib0075 article-title: Semi-supervised learning with deep generative models publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – year: 2015 ident: bib0283 article-title: Semantic image segmentation with deep convolutional nets and fully connected crfs publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 2351 year: 2016 end-page: 2359 ident: bib0212 article-title: Adaptive object detection using adjacency and zoom prediction publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 3084 year: 2013 end-page: 3092 ident: bib0091 article-title: Adaptive dropout for training deep neural networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – year: 2015 ident: bib0252 article-title: Deep gaze i: boosting saliency prediction with feature maps trained on imagenet publication-title: Proceedings of the International Conference on Learning Representations (ICLR) Workshops – start-page: 1666 year: 2015 end-page: 1674 ident: bib0186 article-title: Deep lac: deep localization, alignment and classification for fine-grained recognition publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 92 start-page: 33 year: 2017 end-page: 40 ident: bib0264 article-title: Three-stream CNNs for action recognition publication-title: Pattern Recognit. Lett. – volume: 29 start-page: 141 year: 2012 end-page: 142 ident: bib0062 article-title: The mnist database of handwritten digit images for machine learning research publication-title: IEEE Signal Process. Mag. – start-page: 1060 year: 2016 end-page: 1069 ident: bib0085 article-title: Generative adversarial text to image synthesis publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 1 start-page: 445 year: 1988 end-page: 448 ident: bib0005 article-title: Theory of the backpropagation neural network publication-title: Neural Networks – year: 2017 ident: bib0307 article-title: An empirical study of language CNN for image captioning publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – volume: 63 start-page: 499 year: 2017 end-page: 510 ident: bib0080 article-title: Rodeo: robust de-aliasing autoencoder for real-time medical image reconstruction publication-title: Pattern Recognit. – reference: B. Shuai, Z. Zuo, W. Gang, Quaddirectional 2d-recurrent neural networks for image labeling 22(11) (2015b) 1990–1994. – volume: 12 start-page: 2493 year: 2011 end-page: 2537 ident: bib0314 article-title: Natural language processing (almost) from scratch publication-title: J. Mach. Learn. Res. (JMLR) – start-page: 1232 year: 2012 end-page: 1240 ident: bib0114 article-title: Large scale distributed deep networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 597 year: 2015 end-page: 606 ident: bib0219 article-title: Online tracking by learning discriminative saliency map with convolutional neural network publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 39 start-page: 1677 year: 1991 end-page: 1681 ident: bib0285 article-title: Phonemic hidden ,Markov models with continuous mixture output densities for large vocabulary word recognition publication-title: IEEE Trans. Signal Process. – volume: 48 start-page: 3542 year: 2015 end-page: 3559 ident: bib0194 article-title: Feature representation for statistical-learning-based object detection: a review publication-title: Pattern Recognit. – volume: 37 start-page: 1904 year: 2015 end-page: 1916 ident: bib0203 article-title: Spatial pyramid pooling in deep convolutional networks for visual recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – volume: 111 start-page: 98 year: 2015 end-page: 136 ident: bib0172 article-title: The pascal visual object classes challenge: a retrospective publication-title: Int. J. Conflict Violence (IJCV) – start-page: 1319 year: 2013 end-page: 1327 ident: bib0059 article-title: Maxout networks publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 177 year: 2014 end-page: 186 ident: bib0176 article-title: Error-driven incremental learning in deep convolutional neural network for large-scale image classification publication-title: Proceedings of the ACM Multimedia Conference – reference: X. Chen, A.L. Yuille, Articulated pose estimation by a graphical model with image dependent pairwise relations, in: Proceedings of the Advances in Neural Information Processing Systems (NIPS), 2014, pp. 1736–1744. – volume: 60 start-page: 86 year: 2016 end-page: 105 ident: bib0256 article-title: Rgb-d-based action recognition datasets: a survey publication-title: Pattern Recognit. – year: 2015 ident: bib0101 article-title: The loss surfaces of multilayer networks publication-title: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) – year: 2016 ident: bib0038 article-title: Neural machine translation in linear time publication-title: CoRR abs/1610.10099 – reference: Z. Yan, V. Jagadeesh, D. DeCoste, W. Di, R. Piramuthu, Hd-cnn: hierarchical deep convolutional neural network for image classification, in: Proceedings of the International Conference on Computer Vision (ICCV), pp. 2740–2748. – volume: 39 start-page: 677 year: 2017 end-page: 691 ident: bib0270 article-title: Long-term recurrent convolutional networks for visual recognition and description publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) – year: 2015 ident: bib0009 article-title: Very deep convolutional networks for large-scale image recognition publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – year: 2013 ident: bib0060 article-title: Improving deep neural networks with probabilistic maxout units publication-title: CoRR abs/1312.6116 – year: 2016 ident: bib0040 article-title: Dense prediction on sequences with time-dilated convolutions for speech recognition publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) Workshops – year: 2017 ident: bib0301 article-title: Hierarchical bayesian combination of plug-in maximum a posteriori decoders in deep neural networks-based speech recognition and speaker adaptation publication-title: Pattern Recognit. Lett. – volume: 104 start-page: 154 year: 2013 end-page: 171 ident: bib0185 article-title: Selective search for object recognition publication-title: Int. J. Conflict Violence (IJCV) – year: 2017 ident: bib0167 article-title: Lcnn: Lookup-based convolutional neural network publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – year: 2016 ident: bib0058 article-title: Fast and accurate deep network learning by exponential linear units (elus) publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – volume: 85 year: 2013 ident: bib0141 article-title: Fastfood-approximating kernel expansions in loglinear time publication-title: Proceedings of the International Conference on Machine Learning (ICML) – year: 2015 ident: bib0240 article-title: Deep structured output learning for unconstrained text recognition publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 658 year: 2016 end-page: 666 ident: bib0088 article-title: Generating images with perceptual similarity metrics based on deep networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – year: 2016 ident: bib0102 article-title: All you need is a good init publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – year: 2015 ident: bib0024 article-title: Encoding time series as images for visual inspection and classification using tiled convolutional neural networks publication-title: Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) Workshops – start-page: 2672 year: 2014 end-page: 2680 ident: bib0076 article-title: Generative adversarial nets publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 47 start-page: 3343 year: 2014 end-page: 3361 ident: bib0254 article-title: A survey on still image based human action recognition publication-title: Pattern Recognit. – volume: 29 start-page: 82 year: 2012 end-page: 97 ident: bib0286 article-title: Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups publication-title: IEEE Signal Process. Mag. – start-page: 366 year: 2012 end-page: 369 ident: bib0288 article-title: Adaptation of context-dependent deep neural networks for automatic speech recognition publication-title: Proceedings of the Spoken Language Technology (SLT) – start-page: 2659 year: 2015 end-page: 2667 ident: bib0206 article-title: Attentionnet: Aggregating weak directions for accurate object detection publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 6655 year: 2013 end-page: 6659 ident: bib0134 article-title: Low-rank matrix factorization for deep neural network training with high-dimensional output targets publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – reference: Y. Gong, L. Liu, M. Yang, L. Bourdev, Compressing deep convolutional networks using vector quantization, in: arXiv preprint – year: 2014 ident: bib0239 article-title: Multi-digit number recognition from street view imagery using deep convolutional neural networks publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – volume: 12 start-page: 2451 year: 2000 end-page: 2471 ident: bib0242 article-title: Learning to forget: continual prediction with lstm publication-title: Neural Comput. – start-page: 4249 year: 2015 end-page: 4258 ident: bib0279 article-title: Integrating parametric and non-parametric models for scene labeling publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 35 start-page: 1433 year: 2002 end-page: 1446 ident: bib0230 article-title: A survey on off-line cursive word recognition publication-title: Pattern Recognit. – volume: 32 start-page: 1627 year: 2010 end-page: 1645 ident: bib0207 article-title: Object detection with discriminatively trained part-based models publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – start-page: 9 year: 2012 end-page: 48 ident: bib0013 article-title: Efficient backprop publication-title: Neural Networks: Tricks of the Trade - Second Edition – start-page: 21 year: 2016 end-page: 37 ident: bib0211 article-title: SSD: single shot multibox detector publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – start-page: 307 year: 2014 end-page: 315 ident: bib0044 article-title: Signal recovery from pooling representations publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 46 start-page: 397 year: 2013 end-page: 411 ident: bib0213 article-title: Real-time visual tracking via online weighted multiple instance learning publication-title: Pattern Recognit. – start-page: 3483 year: 2015 end-page: 3491 ident: bib0084 article-title: Learning structured output representation using deep conditional generative models publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1395 year: 2015 end-page: 1403 ident: bib0094 article-title: Holistically-nested edge detection publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – year: 2014 ident: bib0073 article-title: Auto-encoding variational bayes publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – volume: 61 start-page: 610 year: 2017 end-page: 628 ident: bib0171 article-title: Facial expression recognition with convolutional neural networks: coping with few data and the training sample order publication-title: Pattern Recognit. – start-page: 1 year: 2015 end-page: 9 ident: bib0010 article-title: Going deeper with convolutions publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 48 start-page: 2993 year: 2015 end-page: 3003 ident: bib0071 article-title: Deep feature learning with relative distance comparison for person re-identification publication-title: Pattern Recognit. – year: 2013 ident: bib0047 article-title: Stochastic pooling for regularization of deep convolutional neural networks publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 177 year: 1988 end-page: 185 ident: bib0155 article-title: Comparing biases for minimal network construction with back-propagation publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1347 year: 2015 end-page: 1355 ident: bib0227 article-title: Combining local appearance and holistic view: dual-source deep neural networks for human pose estimation publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 932 year: 2016 end-page: 937 ident: bib0035 article-title: Human attention in visual question answering: Do humans and deep networks look at the same regions? publication-title: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) – volume: 48 start-page: 1844 year: 2015 end-page: 1853 ident: bib0195 article-title: A coarse-to-fine approach for fast deformable object detection publication-title: Pattern Recognit. – start-page: 1567 year: 2015 end-page: 1576 ident: bib0306 article-title: cnn: a convolutional architecture for word sequence prediction publication-title: Proceedings of the Association for Computational Linguistics (ACL) – start-page: 1954 year: 2014 end-page: 1958 ident: bib0299 article-title: Dnn-based stochastic postfilter for hmm-based speech synthesis. publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – start-page: 1096 year: 2016 end-page: 1104 ident: bib0072 article-title: Deepfashion: powering robust clothes recognition and retrieval with rich annotations publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 46 start-page: 1772 year: 2013 end-page: 1788 ident: bib0214 article-title: Sparse coding based visual tracking: review and experimental comparison publication-title: Pattern Recognit. – start-page: 2059 year: 2017 end-page: 2065 ident: bib0074 article-title: Denoising criterion for variational auto-encoding framework publication-title: Proceedings of the Association for the Advancement of Artificial Intelligence (AAAI) – start-page: 2148 year: 2013 end-page: 2156 ident: bib0136 article-title: Predicting parameters in deep learning publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 45 start-page: 1318 year: 2012 end-page: 1325 ident: bib0007 article-title: A novel hybrid CNN–SVM classifier for recognizing handwritten digits publication-title: Pattern Recognit. – year: 2016 ident: bib0127 article-title: Resnet in resnet: generalizing residual architectures publication-title: CoRR – start-page: 1449 year: 2015 end-page: 1457 ident: bib0192 article-title: Bilinear CNN models for fine-grained visual recognition publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – volume: 48 start-page: 580 year: 2015 end-page: 590 ident: bib0215 article-title: Multi-target tracking by learning local-to-global trajectory models publication-title: Pattern Recognit. – year: 2014 ident: bib0018 article-title: Network in network publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 392 year: 2014 end-page: 407 ident: bib0052 article-title: Multi-scale orderless pooling of deep convolutional activation features publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – volume: 33 start-page: 2295 year: 2011 end-page: 2317 ident: bib0140 article-title: Tensor-train decomposition publication-title: SIAM J. Sci. Comput. – volume: 45 start-page: 333 year: 2012 end-page: 345 ident: bib0173 article-title: Semantic hierarchies for image annotation: a survey publication-title: Pattern Recognit. – start-page: 2524 year: 2015 end-page: 2532 ident: bib0100 article-title: Augmenting strong supervision using web data for fine-grained categorization publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 936 year: 2016 end-page: 941 ident: bib0124 article-title: Weighted residuals for very deep networks publication-title: Proceedings of the International Conference on Systems and Informatics (ICSAI) – start-page: 801 year: 2006 end-page: 808 ident: bib0082 article-title: Efficient sparse coding algorithms publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 3376 year: 2015 end-page: 3385 ident: bib0282 article-title: Feedforward semantic segmentation with zoom-out features publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 2470 year: 2015 end-page: 2478 ident: bib0259 article-title: Actions and attributes from wholes and parts publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – year: 2014 ident: bib0290 article-title: Convolutional neural networks for speech recognition publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – year: 2017 ident: bib0110 article-title: Sgdr: Stochastic gradient descent with warm restarts publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – year: 2015 ident: bib0029 article-title: Reseg: a recurrent neural network for object segmentation publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops – year: 2015 ident: bib0057 article-title: Empirical evaluation of rectified activations in convolutional network publication-title: Proceedings of the International Conference on Machine Learning (ICML) Workshop – volume: 42 start-page: 1365 year: 1996 end-page: 1374 ident: bib0151 article-title: Efficient scalar quantization of exponential and Laplacian random variables publication-title: IEEE Trans. Inf. Theory – start-page: 302 year: 2014 end-page: 315 ident: bib0228 article-title: Modeep: A deep learning framework using motion features for human pose estimation publication-title: Proceedings of the Asian Conference on Computer Vision (ACCV) – volume: 25 start-page: 5479 year: 2016 end-page: 5490 ident: bib0263 article-title: Action recognition in still images with minimum annotation efforts publication-title: IEEE Trans. Image Process. – volume: 37 start-page: 977 year: 2004 end-page: 997 ident: bib0231 article-title: Text information extraction in images and video: a survey publication-title: Pattern Recognit. – start-page: 343 year: 2013 end-page: 351 ident: bib0111 article-title: No more pesky learning rates publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 946 year: 2014 end-page: 954 ident: bib0143 article-title: Circulant binary embedding publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 1747 year: 2016 end-page: 1756 ident: bib0302 article-title: Pixel recurrent neural networks publication-title: Proceedings of the International Conference on Machine Learning (ICML) – year: 2004 ident: bib0061 article-title: Solving large scale linear prediction problems using stochastic gradient descent algorithms publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 1799 year: 2014 end-page: 1807 ident: bib0224 article-title: Joint training of a convolutional network and a graphical model for human pose estimation publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 12 start-page: 145 year: 1999 end-page: 151 ident: bib0108 article-title: On the momentum term in gradient descent learning algorithms publication-title: Neural Netw. – start-page: 2528 year: 2010 end-page: 2535 ident: bib0026 article-title: Deconvolutional networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 693 year: 2011 end-page: 701 ident: bib0113 article-title: Hogwild: a lock-free approach to parallelizing stochastic gradient descent publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 2019 year: 2014 end-page: 2026 ident: bib0178 article-title: Birdsnap: large-scale fine-grained visual categorization of birds publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 36 start-page: 222 year: 2014 end-page: 234 ident: bib0200 article-title: Category independent object proposals publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – start-page: 4685 year: 2015 end-page: 4693 ident: bib0093 article-title: Mirror, mirror on the wall, tell me, is the error small? publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 39 start-page: 640 year: 2017 end-page: 651 ident: bib0028 article-title: Fully convolutional networks for semantic segmentation publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) – start-page: 818 year: 2014 end-page: 833 ident: bib0011 article-title: Visualizing and understanding convolutional networks publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – start-page: 133 year: 2017 end-page: 141 ident: bib0068 article-title: Deephash: getting regularization, depth and fine-tuning right publication-title: Proceedings of the International Conference on Multimedia Retrieval (ICMR) – volume: PP start-page: 1 year: 2016 ident: bib0128 article-title: Residual networks of residual networks: multilevel residual networks publication-title: IEEE Trans. Circuits Syst. Video Technol. (TCSVT) – start-page: 2449 year: 2015 end-page: 2457 ident: bib0048 article-title: Spectral representations for convolutional neural networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 2798 year: 2014 end-page: 2805 ident: bib0251 article-title: Large-scale optimization of hierarchical features for saliency prediction in natural images publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 5546 year: 2015 end-page: 5555 ident: bib0189 article-title: Fine-grained recognition without part annotations publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 87.1 year: 2016 end-page: 87.12 ident: bib0125 article-title: Wide residual networks publication-title: Proceedings of the British Machine Vision Conference (BMVC) – start-page: 3945 year: 2015 end-page: 3954 ident: bib0226 article-title: Parsing occluded people by flexible compositions publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 1139 year: 2013 end-page: 1147 ident: bib0103 article-title: On the importance of initialization and momentum in deep learning publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 342 year: 2016 end-page: 350 ident: bib0098 article-title: Dreaming more data: Class-dependent distributions over diffeomorphisms for learned data augmentation publication-title: Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) – volume: 29 start-page: 1931 year: 1996 end-page: 1952 ident: bib0229 article-title: Automatic document processing: a survey publication-title: Pattern Recognit. – start-page: 160 year: 2008 end-page: 167 ident: bib0309 article-title: A unified architecture for natural language processing: deep neural networks with multitask learning publication-title: Proceedings of the International Conference on Machine Learning (ICML) – reference: J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, T. Darrell, Decaf: a deep convolutional activation feature for generic visual recognition, 2014. – start-page: 779 year: 2016 end-page: 788 ident: bib0210 article-title: You only look once: unified, real-time object detection publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 507 year: 2016 end-page: 516 ident: bib0063 article-title: Large-margin softmax loss for convolutional neural networks publication-title: Proceedings of the International Conference on Machine Learning (ICML) – year: 2015 ident: bib0243 article-title: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition publication-title: CoRR abs/1507.05717 – start-page: 655 year: 2014 end-page: 665 ident: bib0311 article-title: A convolutional neural network for modelling sentences publication-title: Proceedings of the Association for Computational Linguistics (ACL) – start-page: 1269 year: 2014 end-page: 1277 ident: bib0137 article-title: Exploiting linear structure within convolutional networks for efficient evaluation publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 437 year: 2015 end-page: 446 ident: bib0197 article-title: Deformable part models are convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 396 year: 1989 end-page: 404 ident: bib0003 article-title: Handwritten digit recognition with a back-propagation network publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 67 start-page: 85 year: 2017 end-page: 96 ident: bib0234 article-title: Improving patch-based scene text script identification with ensembles of conjoined networks publication-title: Pattern Recognit. – start-page: 298 year: 2014 end-page: 310 ident: bib0025 article-title: Time series classification using multi-channels deep convolutional neural networks publication-title: Proceedings of the International Conference on Web-Age Information Management (WAIM) – start-page: 4013 year: 2016 end-page: 4021 ident: bib0133 article-title: Fast algorithms for convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 1520 year: 2015 end-page: 1528 ident: bib0030 article-title: Learning deconvolution network for semantic segmentation publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – year: 2014 ident: bib0105 article-title: Exact solutions to the nonlinear dynamics of learning in deep linear neural networks publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 204 year: 2015 end-page: 214 ident: bib0313 article-title: Multichannel variable-size convolution for sentence classification publication-title: Proceedings of the Conference on Natural Language Learning (CoNLL) – year: 2017 ident: bib0119 article-title: Understanding deep learning requires rethinking generalization publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – year: 2013 ident: bib0019 article-title: Deep learning using linear support vector machines publication-title: Proceedings of the International Conference on Machine Learning (ICML) Workshops – start-page: 761 year: 2016 end-page: 769 ident: bib0209 article-title: Training region-based object detectors with online hard example mining publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 539 year: 2005 end-page: 546 ident: bib0065 article-title: Learning a similarity metric discriminatively, with application to face verification publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 64 start-page: 1 year: 2017 end-page: 14 ident: bib0232 article-title: A comprehensive survey of mostly textual document segmentation algorithms since 2008 publication-title: Pattern Recognit. – start-page: 1135 year: 2015 end-page: 1143 ident: bib0156 article-title: Learning both weights and connections for efficient neural network publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 115 start-page: 330 year: 2015 end-page: 344 ident: bib0250 article-title: Supercnn: a superpixelwise convolutional neural network for salient object detection publication-title: Inter. J. Comput. Vis. – year: 2016 ident: bib0145 article-title: Acdc: a structured efficient linear layer publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 1717 year: 2014 end-page: 1724 ident: bib0258 article-title: Learning and transferring mid-level image representations using convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 46 start-page: 1020 year: 2013 end-page: 1038 ident: bib0275 article-title: A survey of graph theoretical approaches to image segmentation publication-title: Pattern Recognit. – year: 2016 ident: bib0037 article-title: Multi-scale context aggregation by dilated convolutions publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 933 year: 2017 end-page: 941 ident: bib0308 article-title: Language modeling with gated convolutional networks publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 2226 year: 2016 end-page: 2234 ident: bib0087 article-title: Improved techniques for training GANs publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1422 year: 2015 end-page: 1430 ident: bib0106 article-title: Unsupervised visual representation learning by context prediction publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 53 year: 2012 end-page: 67 ident: bib0118 article-title: Early stopping - but when? publication-title: Neural Networks: Tricks of the Trade - Second Edition – start-page: 8604 year: 2013 end-page: 8608 ident: bib0287 article-title: Recent advances in deep learning for speech research at Microsoft publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – volume: 21 start-page: 1610 year: 2010 end-page: 1623 ident: bib0216 article-title: Human tracking using convolutional neural networks publication-title: IEEE Trans. Neural Netw. (TNN) – start-page: 364 year: 2014 end-page: 375 ident: bib0046 article-title: Mixed pooling for convolutional neural networks publication-title: Proceedings of the Rough Sets and Knowledge Technology (RSKT) – year: 2014 ident: bib0208 article-title: Fracking deep convolutional image descriptors publication-title: CoRR abs/1412.6537 – year: 2015 ident: bib0161 article-title: Diversity networks publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – volume: 35 start-page: 1915 year: 2013 end-page: 1929 ident: bib0276 article-title: Learning hierarchical features for scene labeling publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – start-page: 630 year: 2016 end-page: 645 ident: bib0123 article-title: Identity mappings in deep residual networks publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – year: 2016 ident: bib0147 article-title: Bitwise neural networks publication-title: Proceedings of the International Conference on Machine Learning (ICML) Workshops – year: 2016 ident: bib0315 article-title: Very deep convolutional networks for natural language processing publication-title: CoRR abs/1606.01781 – start-page: 267 year: 1982 end-page: 285 ident: bib0002 article-title: Neocognitron: a self-organizing neural network model for a mechanism of visual pattern recognition publication-title: Competition and Cooperation in Neural Nets – start-page: 3183 year: 2015 end-page: 3192 ident: bib0246 article-title: Deep networks for saliency detection via local estimation and global search publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 2018 year: 2011 end-page: 2025 ident: bib0027 article-title: Adaptive deconvolutional networks for mid and high level feature learning publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 1653 year: 2014 end-page: 1660 ident: bib0222 article-title: Deeppose: human pose estimation via deep neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 86 start-page: 2278 year: 1998 end-page: 2324 ident: bib0004 article-title: Gradient-based learning applied to document recognition publication-title: Proc. IEEE – start-page: 1486 year: 2015 end-page: 1494 ident: bib0086 article-title: Deep generative image models using a Laplacian pyramid of adversarial networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 38 start-page: 295 year: 2016 end-page: 307 ident: bib0036 article-title: Image super-resolution using deep convolutional networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) – start-page: 3501 year: 2016 end-page: 3508 ident: bib0241 article-title: Reading scene text in deep convolutional sequences publication-title: Proceedings of the AAAI Conference on Artificial Intelligence – year: 2015 ident: bib0253 article-title: End-to-end convolutional network for saliency prediction publication-title: CoRR abs/1507.01422 – reference: H. Hu, R. Peng, Y.-W. Tai, C.-K. Tang, Network trimming: a data-driven neuron pruning approach towards efficient deep architectures, volume abs/1607.03250, 2016. – volume: 59 start-page: 312 year: 2016 end-page: 324 ident: bib0272 article-title: Multi-scale context for scene labeling via flexible segmentation graph publication-title: Pattern Recognit. – start-page: 1096 year: 2008 end-page: 1103 ident: bib0078 article-title: Extracting and composing robust features with denoising autoencoders publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 3225 year: 2016 end-page: 3233 ident: bib0083 article-title: Attend, infer, repeat: fast scene understanding with generative models publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 685 year: 2015 end-page: 693 ident: bib0112 article-title: Deep learning with elastic averaging SGD publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – year: 2014 ident: bib0310 article-title: Deep learning for answer sentence selection publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) Workshop – year: 2014 ident: bib0049 article-title: Fast training of convolutional networks through FFTs publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 648 year: 2015 end-page: 656 ident: bib0092 article-title: Efficient object localization using convolutional networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 3218 year: 2015 end-page: 3226 ident: bib0269 article-title: P-CNN: pose-based CNN features for action recognition publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 3646 year: 2014 end-page: 3653 ident: bib0097 article-title: Transformation pursuit for image classification publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 2167 year: 2016 end-page: 2175 ident: bib0070 article-title: Deep relative distance learning: tell the difference between similar vehicles publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 543 year: 2016 end-page: 559 ident: bib0032 article-title: Top-down neural attention by excitation backprop publication-title: Proceedings of the European Conference on Computer Vision (ECCV) – year: 2015 ident: bib0109 article-title: Adam: A method for stochastic optimization publication-title: Proceedings of the International Conference on Learning Representations (ICLR) – start-page: 1073 year: 2011 end-page: 1081 ident: bib0142 article-title: Fast locality-sensitive hashing publication-title: Proceedings of the International Conference on Knowledge Discovery and Data Mining (SIGKDD) – start-page: 424 year: 2010 end-page: 427 ident: bib0021 article-title: Fast training of object detection using stochastic gradient descent publication-title: International Conference on Pattern Recognition (ICPR) – start-page: 111 year: 2010 end-page: 118 ident: bib0016 article-title: A theoretical analysis of feature pooling in visual recognition publication-title: Proceedings of the International Conference on Machine Learning (ICML) – volume: 26 start-page: 289 year: 2007 end-page: 315 ident: bib0117 article-title: On early stopping in gradient descent learning publication-title: Constructive Approx. – start-page: 2956 year: 2015 end-page: 2964 ident: bib0031 article-title: Look and think twice: capturing top-down visual attention with feedback convolutional neural networks publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – volume: 37 start-page: 1904 year: 2015 end-page: 1916 ident: bib0050 article-title: Spatial pyramid pooling in deep convolutional networks for visual recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – volume: 38 start-page: 1088 year: 2016 end-page: 1098 ident: bib0218 article-title: Cnntracker: online discriminative object tracking via deep convolutional neural network publication-title: Appl. Soft Comput. – year: 2014 ident: bib0077 article-title: Conditional generative adversarial nets publication-title: CoRR abs/1411.1784 – volume: 141 start-page: 245 year: 1994 end-page: 250 ident: bib0198 article-title: Original approach for the localisation of objects in images publication-title: IEE Proc.-Vis. Image Signal Process. – start-page: 4277 year: 2012 end-page: 4280 ident: bib0289 article-title: Applying convolutional neural networks concepts to hybrid nn-hmm model for speech recognition publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – volume: 25 start-page: 1713 year: 2016 end-page: 1725 ident: bib0190 article-title: Weakly supervised fine-grained categorization with part-based image representation publication-title: IEEE Trans. Image Process. – start-page: 448 year: 2015 end-page: 456 ident: bib0120 article-title: Batch normalization: accelerating deep network training by reducing internal covariate shift publication-title: J. Mach. Learn. Res. (JMLR) – start-page: 1265 year: 2015 end-page: 1274 ident: bib0247 article-title: Saliency detection by multi-context deep learning publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 5455 year: 2015 end-page: 5463 ident: bib0248 article-title: Visual saliency based on multiscale deep features publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 442 year: 2015 end-page: 450 ident: bib0139 article-title: Tensorizing neural networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 1058 year: 2013 end-page: 1066 ident: bib0045 article-title: Regularization of neural networks using dropconnect publication-title: Proceedings of the International Conference on Machine Learning (ICML) – start-page: 568 year: 2014 end-page: 576 ident: bib0268 article-title: Two-stream convolutional networks for action recognition in videos publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – start-page: 2074 year: 2016 end-page: 2082 ident: bib0166 article-title: Learning structured sparsity in deep neural networks publication-title: Proceedings of the Advances in Neural Information Processing Systems (NIPS) – volume: 81 start-page: 80 year: 2016 end-page: 89 ident: bib0181 article-title: Finely-grained annotated datasets for image-based plant phenotyping publication-title: Pattern Recognit. Lett. – volume: 34 start-page: 1704 year: 2012 end-page: 1716 ident: bib0053 article-title: Aggregating local image descriptors into compact codes publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) – year: 2016 ident: bib0149 article-title: Dorefa-net: training low bitwidth convolutional neural networks with low bitwidth gradients publication-title: CoRR – volume: 39 start-page: 195 year: 1943 end-page: 198 ident: bib0089 article-title: On the stability of inverse problems publication-title: Dokl. Akad. Nauk SSSR – volume: 35 start-page: 221 year: 2013 end-page: 231 ident: bib0265 article-title: 3D convolutional neural networks for human action recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) – volume: 37 start-page: 328 year: 1989 end-page: 339 ident: bib0298 article-title: Phoneme recognition using time-delay neural networks publication-title: IEEE Trans. Acoustics, Speech, Signal Process. – volume: 48 start-page: 2983 year: 2015 end-page: 2992 ident: bib0273 article-title: CRF learning with CNN features for image segmentation publication-title: Pattern Recognit. – start-page: 1026 year: 2015 end-page: 1034 ident: bib0056 article-title: Delving deep into rectifiers: Surpassing human-level performance on imagenet classification publication-title: Proceedings of the International Conference on Computer Vision (ICCV) – start-page: 1766 year: 2013 end-page: 1770 ident: bib0291 article-title: Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – start-page: 4465 year: 2015 end-page: 4469 ident: bib0300 article-title: Modelling acoustic feature dependencies with artificial neural networks: Trajectory-rnade publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – volume: 381 start-page: 607 year: 1996 ident: bib0081 article-title: Emergence of simple-cell receptive field properties by learning a sparse code for natural images publication-title: Nature – start-page: 2818 year: 2016 end-page: 2826 ident: bib0041 article-title: Rethinking the inception architecture for computer vision publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – volume: 115 start-page: 211 year: 2015 end-page: 252 ident: bib0008 article-title: Imagenet large scale visual recognition challenge publication-title: Int. J. Conflict Violence (IJCV) – start-page: 17 year: 2016 end-page: 21 ident: bib0297 article-title: Deep convolutional neural networks with layer-wise context expansion and attention publication-title: Proceedings of the International Speech Communication Association (INTERSPEECH) – volume: 29 start-page: 4790 year: 1990 end-page: 4797 ident: bib0006 article-title: Parallel distributed processing model with local space-invariant interconnections and its optical architecture publication-title: Appl. Opt. – start-page: 362 year: 2015 end-page: 370 ident: bib0249 article-title: Predicting eye fixations using convolutional neural networks publication-title: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) – start-page: 4624 year: 2015 end-page: 4628 ident: bib0292 article-title: Speech acoustic modeling from raw multichannel waveforms publication-title: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) – year: 2014 ident: bib0138 article-title: Speeding up convolutional neural networks with low rank expansions publication-title: Proceedings of the British Machine Vision Conference (BMVC) – volume: 37 start-page: 1904 issue: 9 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0050 article-title: Spatial pyramid pooling in deep convolutional networks for visual recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2015.2389824 – start-page: 901 year: 1994 ident: 10.1016/j.patcog.2017.10.013_bib0196 article-title: A convolutional neural network hand tracker – volume: 29 start-page: 1931 issue: 12 year: 1996 ident: 10.1016/j.patcog.2017.10.013_bib0229 article-title: Automatic document processing: a survey publication-title: Pattern Recognit. doi: 10.1016/S0031-3203(96)00044-1 – start-page: 1449 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0192 article-title: Bilinear CNN models for fine-grained visual recognition – start-page: 761 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0209 article-title: Training region-based object detectors with online hard example mining – start-page: 2528 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0026 article-title: Deconvolutional networks – year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0277 article-title: Indoor semantic segmentation using depth information – start-page: 806 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0165 article-title: Sparse convolutional neural networks – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0018 article-title: Network in network – start-page: 249 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0104 article-title: Understanding the difficulty of training deep feedforward neural networks – start-page: 37 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0107 article-title: Learning to see by moving – start-page: 1520 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0030 article-title: Learning deconvolution network for semantic segmentation – volume: 35 start-page: 2279 issue: 10 year: 2002 ident: 10.1016/j.patcog.2017.10.013_bib0168 article-title: Image processing with neural networksa review publication-title: Pattern Recognit. doi: 10.1016/S0031-3203(01)00178-9 – ident: 10.1016/j.patcog.2017.10.013_bib0293 – volume: 33 start-page: 2295 issue: 5 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0140 article-title: Tensor-train decomposition publication-title: SIAM J. Sci. Comput. doi: 10.1137/090752286 – start-page: 3501 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0241 article-title: Reading scene text in deep convolutional sequences – start-page: 3581 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0075 article-title: Semi-supervised learning with deep generative models – start-page: 1058 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0045 article-title: Regularization of neural networks using dropconnect – start-page: 204 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0313 article-title: Multichannel variable-size convolution for sentence classification – ident: 10.1016/j.patcog.2017.10.013_bib0132 – start-page: 267 year: 1982 ident: 10.1016/j.patcog.2017.10.013_bib0002 article-title: Neocognitron: a self-organizing neural network model for a mechanism of visual pattern recognition – volume: 115 start-page: 211 issue: 3 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0008 article-title: Imagenet large scale visual recognition challenge publication-title: Int. J. Conflict Violence (IJCV) – start-page: 1096 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0072 article-title: Deepfashion: powering robust clothes recognition and retrieval with rich annotations – start-page: 815 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0069 article-title: Facenet: a unified embedding for face recognition and clustering – start-page: 160 year: 2008 ident: 10.1016/j.patcog.2017.10.013_bib0309 article-title: A unified architecture for natural language processing: deep neural networks with multitask learning – year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0060 article-title: Improving deep neural networks with probabilistic maxout units publication-title: CoRR abs/1312.6116 – start-page: 302 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0228 article-title: Modeep: A deep learning framework using motion features for human pose estimation – start-page: 3304 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0015 article-title: End-to-end text recognition with convolutional neural networks – start-page: 4278 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0042 article-title: Inception-v4, inception-resnet and the impact of residual connections on learning – start-page: 1134 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0205 article-title: Object detection via a multi-region and semantic segmentation-aware cnn model – start-page: 2285 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0162 article-title: Compressing neural networks with the hashing trick – start-page: 646 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0316 article-title: Deep networks with stochastic depth – volume: 60 start-page: 875 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0079 article-title: Dual autoencoders features for imbalance classification problem publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.06.013 – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0243 article-title: An end-to-end trainable neural network for image-based sequence recognition and its application to scene text recognition publication-title: CoRR abs/1507.05717 – volume: 12 start-page: 2493 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0314 article-title: Natural language processing (almost) from scratch publication-title: J. Mach. Learn. Res. (JMLR) – volume: PP start-page: 1 issue: 99 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0128 article-title: Residual networks of residual networks: multilevel residual networks publication-title: IEEE Trans. Circuits Syst. Video Technol. (TCSVT) – volume: 115 start-page: 330 issue: 3 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0250 article-title: Supercnn: a superpixelwise convolutional neural network for salient object detection publication-title: Inter. J. Comput. Vis. doi: 10.1007/s11263-015-0822-0 – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0310 article-title: Deep learning for answer sentence selection – start-page: 507 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0063 article-title: Large-margin softmax loss for convolutional neural networks – start-page: 1799 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0224 article-title: Joint training of a convolutional network and a graphical model for human pose estimation – volume: 51 start-page: 148 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0193 article-title: Human detection from images and videos: a survey publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.08.027 – start-page: 315 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0296 article-title: Improvements to deep convolutional neural networks for LVCSR – start-page: 4685 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0093 article-title: Mirror, mirror on the wall, tell me, is the error small? – start-page: 1379 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0157 article-title: Dynamic network surgery for efficient DNNs – volume: 48 start-page: 3004 issue: 10 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0170 article-title: Exemplar based deep discriminative and shareable feature learning for scene image classification publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.02.003 – start-page: 3483 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0084 article-title: Learning structured output representation using deep conditional generative models – start-page: 1279 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0023 article-title: Tiled convolutional neural networks – start-page: 448 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0120 article-title: Batch normalization: accelerating deep network training by reducing internal covariate shift publication-title: J. Mach. Learn. Res. (JMLR) – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0161 article-title: Diversity networks – volume: 45 start-page: 333 issue: 1 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0173 article-title: Semantic hierarchies for image annotation: a survey publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2011.05.017 – start-page: 2672 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0076 article-title: Generative adversarial nets – volume: 35 start-page: 1915 issue: 8 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0276 article-title: Learning hierarchical features for scene labeling publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2012.231 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0315 article-title: Very deep convolutional networks for natural language processing publication-title: CoRR abs/1606.01781 – start-page: 3429 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0294 article-title: Advances in very deep convolutional neural networks for LVCSR – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0073 article-title: Auto-encoding variational bayes – start-page: 3225 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0083 article-title: Attend, infer, repeat: fast scene understanding with generative models – start-page: 658 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0088 article-title: Generating images with perceptual similarity metrics based on deep networks – start-page: 4465 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0300 article-title: Modelling acoustic feature dependencies with artificial neural networks: Trajectory-rnade – start-page: 1766 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0291 article-title: Estimating phoneme class conditional probabilities from raw speech signal using convolutional neural networks – start-page: 568 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0268 article-title: Two-stream convolutional networks for action recognition in videos – volume: 61 start-page: 539 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0169 article-title: Towards better exploiting convolutional neural networks for remote sensing scene classification publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.07.001 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0147 article-title: Bitwise neural networks – ident: 10.1016/j.patcog.2017.10.013_bib0159 – start-page: 1395 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0094 article-title: Holistically-nested edge detection – volume: 39 start-page: 1137 issue: 6 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0204 article-title: Faster r-CNN: towards real-time object detection with region proposal networks publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2016.2577031 – volume: 45 start-page: 3084 issue: 9 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0020 article-title: An extensive experimental comparison of methods for multi-label learning publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2012.03.004 – start-page: 1725 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0267 article-title: Large-scale video classification with convolutional neural networks – volume: 48 start-page: 3542 issue: 11 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0194 article-title: Feature representation for statistical-learning-based object detection: a review publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.04.018 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0303 article-title: Exploring the limits of language modeling – year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0017 article-title: Improving neural networks by preventing co-adaptation of feature detectors publication-title: CoRR abs/1207.0580 – volume: 46 start-page: 1772 issue: 7 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0214 article-title: Sparse coding based visual tracking: review and experimental comparison publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2012.10.006 – start-page: 3945 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0226 article-title: Parsing occluded people by flexible compositions – start-page: 512 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0244 article-title: Deep features for text spotting – start-page: 655 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0311 article-title: A convolutional neural network for modelling sentences – start-page: 1135 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0156 article-title: Learning both weights and connections for efficient neural network – start-page: 366 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0288 article-title: Adaptation of context-dependent deep neural networks for automatic speech recognition – start-page: 2741 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0304 article-title: Character-aware neural language models – start-page: 1567 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0306 article-title: gen cnn: a convolutional architecture for word sequence prediction – volume: 85 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0141 article-title: Fastfood-approximating kernel expansions in loglinear time – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0049 article-title: Fast training of convolutional networks through FFTs – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0307 article-title: An empirical study of language CNN for image captioning – start-page: 1096 year: 2008 ident: 10.1016/j.patcog.2017.10.013_bib0078 article-title: Extracting and composing robust features with denoising autoencoders – volume: 21 start-page: 1610 issue: 10 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0216 article-title: Human tracking using convolutional neural networks publication-title: IEEE Trans. Neural Netw. (TNN) doi: 10.1109/TNN.2010.2066286 – start-page: 82 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0278 article-title: Recurrent convolutional neural networks for scene labeling – start-page: 1232 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0114 article-title: Large scale distributed deep networks – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0221 article-title: Generation of human depth images with body part labels for complex human pose recognition publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.06.006 – volume: 39 start-page: 195 year: 1943 ident: 10.1016/j.patcog.2017.10.013_bib0089 article-title: On the stability of inverse problems – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0167 article-title: Lcnn: Lookup-based convolutional neural network – start-page: 6655 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0134 article-title: Low-rank matrix factorization for deep neural network training with high-dimensional output targets – start-page: 1653 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0222 article-title: Deeppose: human pose estimation via deep neural networks – volume: 45 start-page: 1318 issue: 4 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0007 article-title: A novel hybrid CNN–SVM classifier for recognizing handwritten digits publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2011.09.021 – start-page: 1735 year: 2006 ident: 10.1016/j.patcog.2017.10.013_bib0066 article-title: Dimensionality reduction by learning an invariant mapping – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0223 article-title: Learning human pose estimation features with convolutional networks – start-page: 1026 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0056 article-title: Delving deep into rectifiers: Surpassing human-level performance on imagenet classification – start-page: 290 year: 2008 ident: 10.1016/j.patcog.2017.10.013_bib0235 article-title: Text detection with convolutional neural networks – volume: 35 start-page: 221 issue: 1 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0265 article-title: 3D convolutional neural networks for human action recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2012.59 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0145 article-title: Acdc: a structured efficient linear layer – start-page: 2470 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0259 article-title: Actions and attributes from wholes and parts – volume: 37 start-page: 1904 issue: 9 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0203 article-title: Spatial pyramid pooling in deep convolutional networks for visual recognition publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2015.2389824 – volume: 25 start-page: 5479 issue: 11 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0263 article-title: Action recognition in still images with minimum annotation efforts publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2605305 – start-page: 2365 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0135 article-title: Restructuring of deep neural network acoustic models with singular value decomposition – start-page: 2226 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0087 article-title: Improved techniques for training GANs – start-page: 3084 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0091 article-title: Adaptive dropout for training deep neural networks – year: 2016 ident: 10.1016/j.patcog.2017.10.013_sbref0147 article-title: Dorefa-net: training low bitwidth convolutional neural networks with low bitwidth gradients publication-title: CoRR – volume: 42 start-page: 1365 issue: 5 year: 1996 ident: 10.1016/j.patcog.2017.10.013_bib0151 article-title: Efficient scalar quantization of exponential and Laplacian random variables publication-title: IEEE Trans. Inf. Theory doi: 10.1109/18.532878 – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0301 article-title: Hierarchical bayesian combination of plug-in maximum a posteriori decoders in deep neural networks-based speech recognition and speaker adaptation publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2017.08.001 – start-page: 1747 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0302 article-title: Pixel recurrent neural networks – start-page: 87.1 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0125 article-title: Wide residual networks – start-page: 612 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0033 article-title: Augmenting supervised neural networks with unsupervised objectives for large-scale image classification – start-page: 28 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0126 article-title: Swapout: learning an ensemble of deep architectures – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0029 article-title: Reseg: a recurrent neural network for object segmentation – start-page: 801 year: 2006 ident: 10.1016/j.patcog.2017.10.013_bib0082 article-title: Efficient sparse coding algorithms – start-page: 2094 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0174 article-title: Discriminative transfer learning with tree-based priors – start-page: 2148 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0136 article-title: Predicting parameters in deep learning – start-page: 2059 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0074 article-title: Denoising criterion for variational auto-encoding framework – volume: 71 start-page: 132 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0220 article-title: Head pose estimation in the wild using convolutional neural networks and adaptive gradient methods publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.06.009 – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0067 article-title: Learning by coincidence: siamese networks and common variable learning publication-title: Pattern Recognit. – start-page: 3376 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0282 article-title: Feedforward semantic segmentation with zoom-out features – start-page: 3218 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0269 article-title: P-CNN: pose-based CNN features for action recognition – start-page: 424 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0021 article-title: Fast training of object detection using stochastic gradient descent – start-page: 1954 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0299 article-title: Dnn-based stochastic postfilter for hmm-based speech synthesis. – ident: 10.1016/j.patcog.2017.10.013_bib0257 – year: 2004 ident: 10.1016/j.patcog.2017.10.013_bib0061 article-title: Solving large scale linear prediction problems using stochastic gradient descent algorithms – start-page: 1666 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0186 article-title: Deep lac: deep localization, alignment and classification for fine-grained recognition – start-page: 497 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0237 article-title: Robust scene text detection with convolution neural network induced mser trees – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0101 article-title: The loss surfaces of multilayer networks – start-page: 4489 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0266 article-title: Learning spatiotemporal features with 3d convolutional networks – ident: 10.1016/j.patcog.2017.10.013_bib0305 – start-page: 2659 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0206 article-title: Attentionnet: Aggregating weak directions for accurate object detection – start-page: 1073 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0142 article-title: Fast locality-sensitive hashing – volume: 104 start-page: 154 issue: 2 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0185 article-title: Selective search for object recognition publication-title: Int. J. Conflict Violence (IJCV) – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0009 article-title: Very deep convolutional networks for large-scale image recognition – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0040 article-title: Dense prediction on sequences with time-dilated convolutions for speech recognition – start-page: 2645 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0099 article-title: Hyper-class augmented and regularized deep learning for fine-grained image classification – start-page: 2921 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0034 article-title: Learning deep features for discriminative localization – start-page: 3183 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0246 article-title: Deep networks for saliency detection via local estimation and global search – start-page: 396 year: 1989 ident: 10.1016/j.patcog.2017.10.013_bib0003 article-title: Handwritten digit recognition with a back-propagation network – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0160 article-title: Data-free parameter pruning for deep neural networks – ident: 10.1016/j.patcog.2017.10.013_bib0130 – volume: 37 start-page: 977 issue: 5 year: 2004 ident: 10.1016/j.patcog.2017.10.013_bib0231 article-title: Text information extraction in images and video: a survey publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2003.10.012 – volume: 10 start-page: 11259 issue: 12 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0153 article-title: Approximate nearest neighbor search by residual vector quantization publication-title: Sensors doi: 10.3390/s101211259 – volume: 53 start-page: 130 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0255 article-title: 3D skeleton-based human action classification: a survey publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.11.019 – volume: 46 start-page: 1020 issue: 3 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0275 article-title: A survey of graph theoretical approaches to image segmentation publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2012.09.015 – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0290 article-title: Convolutional neural networks for speech recognition – start-page: 53 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0118 article-title: Early stopping - but when? – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0109 article-title: Adam: A method for stochastic optimization – start-page: 779 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0210 article-title: You only look once: unified, real-time object detection – start-page: 740 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0199 article-title: Microsoft Coco: Common Objects in Context – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0058 article-title: Fast and accurate deep network learning by exponential linear units (elus) – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0175 article-title: Learning fine-grained features via a CNN tree for large-scale classification publication-title: CoRR abs/1511.04534 – start-page: 946 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0143 article-title: Circulant binary embedding – volume: 46 start-page: 397 issue: 1 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0213 article-title: Real-time visual tracking via online weighted multiple instance learning publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2012.07.013 – start-page: 111 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0016 article-title: A theoretical analysis of feature pooling in visual recognition – start-page: 818 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0011 article-title: Visualizing and understanding convolutional networks – volume: 18 start-page: 81 issue: 2 year: 2007 ident: 10.1016/j.patcog.2017.10.013_bib0043 article-title: Complex cell pooling and the statistics of natural images publication-title: Network doi: 10.1080/09548980701418942 – ident: 10.1016/j.patcog.2017.10.013_bib0245 doi: 10.1007/s11263-015-0823-z – start-page: 2857 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0144 article-title: An exploration of parameter redundancy in deep networks with circulant projections – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0183 article-title: Improved bird species recognition using pose normalized deep convolutional nets – start-page: 5455 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0248 article-title: Visual saliency based on multiscale deep features – start-page: 1078 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0295 article-title: Convolutional deep maxout networks for phone recognition. – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0131 article-title: Fast convolutional nets with fbfft: aGPU performance evaluation – start-page: 1060 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0085 article-title: Generative adversarial text to image synthesis – start-page: 8604 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0287 article-title: Recent advances in deep learning for speech research at Microsoft – volume: 71 start-page: 118 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0182 article-title: Lg-cnn: from local parts to global discrimination for fine-grained recognition publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.06.002 – ident: 10.1016/j.patcog.2017.10.013_bib0152 – start-page: 4249 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0279 article-title: Integrating parametric and non-parametric models for scene labeling – volume: 39 start-page: 640 issue: 4 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0028 article-title: Fully convolutional networks for semantic segmentation publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2016.2572683 – start-page: 2524 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0100 article-title: Augmenting strong supervision using web data for fine-grained categorization – volume: 35 start-page: 1433 issue: 7 year: 2002 ident: 10.1016/j.patcog.2017.10.013_bib0230 article-title: A survey on off-line cursive word recognition publication-title: Pattern Recognit. doi: 10.1016/S0031-3203(01)00129-7 – volume: 60 start-page: 86 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0256 article-title: Rgb-d-based action recognition datasets: a survey publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.05.019 – volume: 92 start-page: 33 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0264 article-title: Three-stream CNNs for action recognition publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2017.04.004 – start-page: 648 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0092 article-title: Efficient object localization using convolutional networks – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0077 article-title: Conditional generative adversarial nets publication-title: CoRR abs/1411.1784 – start-page: 442 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0139 article-title: Tensorizing neural networks – volume: 26 start-page: 289 issue: 2 year: 2007 ident: 10.1016/j.patcog.2017.10.013_bib0117 article-title: On early stopping in gradient descent learning publication-title: Constructive Approx. doi: 10.1007/s00365-006-0663-2 – year: 2011 ident: 10.1016/j.patcog.2017.10.013_sbref0115 article-title: GPU asynchronous stochastic gradient descent to speed up neural network training publication-title: CoRR – start-page: 17 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0297 article-title: Deep convolutional neural networks with layer-wise context expansion and attention – start-page: 693 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0113 article-title: Hogwild: a lock-free approach to parallelizing stochastic gradient descent – volume: 2 start-page: 1 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0179 article-title: Novel dataset for fine-grained image categorization: stanford dogs – volume: 48 start-page: 580 issue: 2 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0215 article-title: Multi-target tracking by learning local-to-global trajectory models publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2014.08.013 – start-page: 26 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0188 article-title: Learning features and parts for fine-grained recognition – start-page: 437 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0197 article-title: Deformable part models are convolutional neural networks – start-page: 215 year: 1968 ident: 10.1016/j.patcog.2017.10.013_bib0001 article-title: Receptive fields and functional architecture of monkey striate cortex publication-title: J. Physiol. doi: 10.1113/jphysiol.1968.sp008455 – start-page: 3517 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0055 article-title: On rectified linear units for speech processing – start-page: 543 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0032 article-title: Top-down neural attention by excitation backprop – start-page: 770 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0012 article-title: Deep residual learning for image recognition – start-page: 21 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0211 article-title: SSD: single shot multibox detector – volume: 381 start-page: 607 issue: 6583 year: 1996 ident: 10.1016/j.patcog.2017.10.013_bib0081 article-title: Emergence of simple-cell receptive field properties by learning a sparse code for natural images publication-title: Nature doi: 10.1038/381607a0 – start-page: 2798 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0251 article-title: Large-scale optimization of hierarchical features for saliency prediction in natural images – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0024 article-title: Encoding time series as images for visual inspection and classification using tiled convolutional neural networks – start-page: 2074 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0166 article-title: Learning structured sparsity in deep neural networks – volume: 9 start-page: 1735 issue: 8 year: 1997 ident: 10.1016/j.patcog.2017.10.013_bib0121 article-title: Long short-term memory publication-title: Neural Comput. doi: 10.1162/neco.1997.9.8.1735 – start-page: 2167 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0070 article-title: Deep relative distance learning: tell the difference between similar vehicles – start-page: 1422 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0106 article-title: Unsupervised visual representation learning by context prediction – start-page: 249 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0116 article-title: A fast parallel SGD for matrix factorization in shared memory systems – start-page: 2019 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0178 article-title: Birdsnap: large-scale fine-grained visual categorization of birds – start-page: 1319 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0059 article-title: Maxout networks – start-page: 2018 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0027 article-title: Adaptive deconvolutional networks for mid and high level feature learning – volume: 39 start-page: 1677 issue: 7 year: 1991 ident: 10.1016/j.patcog.2017.10.013_bib0285 article-title: Phonemic hidden ,Markov models with continuous mixture output densities for large vocabulary word recognition publication-title: IEEE Trans. Signal Process. doi: 10.1109/78.134406 – volume: 38 start-page: 295 issue: 2 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0036 article-title: Image super-resolution using deep convolutional networks publication-title: IEEE Trans. Pattern Anal. Mach. Intell. (PAMI) doi: 10.1109/TPAMI.2015.2439281 – start-page: 2449 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0048 article-title: Spectral representations for convolutional neural networks – start-page: 936 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0124 article-title: Weighted residuals for very deep networks – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0150 article-title: Binarynet: training deep neural networks with weights and activations constrained to+ 1 or-1 – start-page: 2956 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0031 article-title: Look and think twice: capturing top-down visual attention with feedback convolutional neural networks – start-page: 307 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0044 article-title: Signal recovery from pooling representations – start-page: 525 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0148 article-title: Xnor-net: imagenet classification using binary convolutional neural networks – start-page: 2377 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0122 article-title: Training very deep networks – start-page: 1265 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0247 article-title: Saliency detection by multi-context deep learning – volume: 1 start-page: 445 issue: Supplement-1 year: 1988 ident: 10.1016/j.patcog.2017.10.013_bib0005 article-title: Theory of the backpropagation neural network publication-title: Neural Networks doi: 10.1016/0893-6080(88)90469-8 – start-page: 1139 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0103 article-title: On the importance of initialization and momentum in deep learning – start-page: 685 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0112 article-title: Deep learning with elastic averaging SGD – volume: 12 start-page: 145 issue: 1 year: 1999 ident: 10.1016/j.patcog.2017.10.013_bib0108 article-title: On the momentum term in gradient descent learning algorithms publication-title: Neural Netw. doi: 10.1016/S0893-6080(98)00116-6 – volume: 48 start-page: 2983 issue: 10 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0273 article-title: CRF learning with CNN features for image segmentation publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.04.019 – start-page: 2650 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0096 article-title: Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture – start-page: 3646 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0097 article-title: Transformation pursuit for image classification – start-page: 177 year: 1988 ident: 10.1016/j.patcog.2017.10.013_bib0155 article-title: Comparing biases for minimal network construction with back-propagation – start-page: 364 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0046 article-title: Mixed pooling for convolutional neural networks – start-page: 807 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0014 article-title: Rectified linear units improve restricted Boltzmann machines – start-page: 118 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0090 article-title: Fast dropout training – start-page: 177 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0176 article-title: Error-driven incremental learning in deep convolutional neural network for large-scale image classification – start-page: 73 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0051 article-title: Unsupervised discovery of mid-level discriminative patches – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0283 article-title: Semantic image segmentation with deep convolutional nets and fully connected crfs – volume: 29 start-page: 141 issue: 6 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0062 article-title: The mnist database of handwritten digit images for machine learning research publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2012.2211477 – start-page: 133 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0068 article-title: Deephash: getting regularization, depth and fine-tuning right – start-page: 2595 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0022 article-title: Parallelized stochastic gradient descent – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0217 article-title: Deeptrack: learning discriminative feature representations by convolutional neural networks for visual tracking – volume: 38 start-page: 1088 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0218 article-title: Cnntracker: online discriminative object tracking via deep convolutional neural network publication-title: Appl. Soft Comput. doi: 10.1016/j.asoc.2015.06.048 – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0252 article-title: Deep gaze i: boosting saliency prediction with feature maps trained on imagenet – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0119 article-title: Understanding deep learning requires rethinking generalization – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0138 article-title: Speeding up convolutional neural networks with low rank expansions – volume: 67 start-page: 85 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0234 article-title: Improving patch-based scene text script identification with ensembles of conjoined networks publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.01.032 – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0239 article-title: Multi-digit number recognition from street view imagery using deep convolutional neural networks – start-page: 4700 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0129 article-title: Densely connected convolutional networks – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0146 article-title: Deep compression: compressing deep neural network with pruning, trained quantization and huffman coding – start-page: 1717 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0258 article-title: Learning and transferring mid-level image representations using convolutional neural networks – start-page: 4277 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0289 article-title: Applying convolutional neural networks concepts to hybrid nn-hmm model for speech recognition – volume: 29 start-page: 82 issue: 6 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0286 article-title: Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups publication-title: IEEE Signal Process. Mag. doi: 10.1109/MSP.2012.2205597 – start-page: 834 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0184 article-title: Part-based r-cnns for fine-grained category detection – volume: 59 start-page: 312 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0272 article-title: Multi-scale context for scene labeling via flexible segmentation graph publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.03.023 – start-page: 1 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0010 article-title: Going deeper with convolutions – volume: 59 start-page: 188 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0274 article-title: Scene parsing using inference embedded deep networks publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.01.027 – volume: 81 start-page: 80 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0181 article-title: Finely-grained annotated datasets for image-based plant phenotyping publication-title: Pattern Recognit. Lett. doi: 10.1016/j.patrec.2015.10.013 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_sbref0127 article-title: Resnet in resnet: generalizing residual architectures publication-title: CoRR – year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0110 article-title: Sgdr: Stochastic gradient descent with warm restarts – start-page: 362 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0249 article-title: Predicting eye fixations using convolutional neural networks – ident: 10.1016/j.patcog.2017.10.013_bib0280 doi: 10.1109/LSP.2015.2441781 – volume: 47 start-page: 3343 issue: 10 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0254 article-title: A survey on still image based human action recognition publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2014.04.018 – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0057 article-title: Empirical evaluation of rectified activations in convolutional network – volume: 37 start-page: 328 issue: 3 year: 1989 ident: 10.1016/j.patcog.2017.10.013_bib0298 article-title: Phoneme recognition using time-delay neural networks publication-title: IEEE Trans. Acoustics, Speech, Signal Process. doi: 10.1109/29.21701 – volume: 86 start-page: 2278 issue: 11 year: 1998 ident: 10.1016/j.patcog.2017.10.013_bib0004 article-title: Gradient-based learning applied to document recognition publication-title: Proc. IEEE doi: 10.1109/5.726791 – start-page: 298 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0025 article-title: Time series classification using multi-channels deep convolutional neural networks – year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0047 article-title: Stochastic pooling for regularization of deep convolutional neural networks – volume: 24 start-page: 279 issue: 3 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0095 article-title: Deep convolutional neural networks and data augmentation for environmental sound classification publication-title: Signal Process. Lett. (SPL) doi: 10.1109/LSP.2017.2657381 – volume: 32 start-page: 1627 issue: 9 year: 2010 ident: 10.1016/j.patcog.2017.10.013_bib0207 article-title: Object detection with discriminatively trained part-based models publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2009.167 – start-page: 932 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0035 article-title: Human attention in visual question answering: Do humans and deep networks look at the same regions? – start-page: 342 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0098 article-title: Dreaming more data: Class-dependent distributions over diffeomorphisms for learned data augmentation – volume: 66 start-page: 437 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0233 article-title: Text/non-text image classification in the wild with convolutional neural networks publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.12.005 – start-page: 2818 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0041 article-title: Rethinking the inception architecture for computer vision – start-page: 169 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0154 article-title: Scalar quantization for large scale image search – start-page: 5546 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0189 article-title: Fine-grained recognition without part annotations – year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0019 article-title: Deep learning using linear support vector machines – start-page: 2470 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0262 article-title: Actions and attributes from wholes and parts – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0102 article-title: All you need is a good init – volume: 29 start-page: 4790 issue: 32 year: 1990 ident: 10.1016/j.patcog.2017.10.013_bib0006 article-title: Parallel distributed processing model with local space-invariant interconnections and its optical architecture publication-title: Appl. Opt. doi: 10.1364/AO.29.004790 – volume: 25 start-page: 1713 issue: 4 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0190 article-title: Weakly supervised fine-grained categorization with part-based image representation publication-title: IEEE Trans. Image Process. doi: 10.1109/TIP.2016.2531289 – start-page: 539 year: 2005 ident: 10.1016/j.patcog.2017.10.013_bib0065 article-title: Learning a similarity metric discriminatively, with application to face verification – start-page: 343 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0111 article-title: No more pesky learning rates – volume: 141 start-page: 245 issue: 4 year: 1994 ident: 10.1016/j.patcog.2017.10.013_bib0198 article-title: Original approach for the localisation of objects in images publication-title: IEE Proc.-Vis. Image Signal Process. doi: 10.1049/ip-vis:19941301 – start-page: 597 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0219 article-title: Online tracking by learning discriminative saliency map with convolutional neural network – start-page: 1486 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0086 article-title: Deep generative image models using a Laplacian pyramid of adversarial networks – start-page: 630 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0123 article-title: Identity mappings in deep residual networks – start-page: 886 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0238 article-title: Automatic discrimination of text and non-text natural images – volume: 10 start-page: 2615 year: 2009 ident: 10.1016/j.patcog.2017.10.013_bib0163 article-title: Hash kernels for structured data publication-title: J. Mach. Learn. Res. (JMLR) – ident: 10.1016/j.patcog.2017.10.013_bib0225 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0037 article-title: Multi-scale context aggregation by dilated convolutions – start-page: 1080 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0261 article-title: Contextual action recognition with rCNN – volume: 63 start-page: 499 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0080 article-title: Rodeo: robust de-aliasing autoencoder for real-time medical image reconstruction publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.09.022 – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0208 article-title: Fracking deep convolutional image descriptors publication-title: CoRR abs/1412.6537 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0158 article-title: Designing energy-efficient convolutional neural networks using energy-aware pruning publication-title: CoRR abs/1611.05128 – start-page: 3973 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0180 article-title: A large-scale car dataset for fine-grained categorization and verification – volume: 30 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0054 article-title: Rectifier nonlinearities improve neural network acoustic models – ident: 10.1016/j.patcog.2017.10.013_bib0177 – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0253 article-title: End-to-end convolutional network for saliency prediction publication-title: CoRR abs/1507.01422 – volume: 34 start-page: 1704 issue: 9 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0053 article-title: Aggregating local image descriptors into compact codes publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2011.235 – volume: 111 start-page: 98 issue: 1 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0172 article-title: The pascal visual object classes challenge: a retrospective publication-title: Int. J. Conflict Violence (IJCV) – volume: 36 start-page: 222 issue: 2 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0200 article-title: Category independent object proposals publication-title: IEEE Trans. Pattern Anal. Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2013.122 – start-page: 4013 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0133 article-title: Fast algorithms for convolutional neural networks – year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0105 article-title: Exact solutions to the nonlinear dynamics of learning in deep linear neural networks – volume: 12 start-page: 2451 issue: 10 year: 2000 ident: 10.1016/j.patcog.2017.10.013_bib0242 article-title: Learning to forget: continual prediction with lstm publication-title: Neural Comput. doi: 10.1162/089976600300015015 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0039 article-title: Wavenet: a generative model for raw audio publication-title: CoRR abs/1609.03499 – start-page: 842 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0191 article-title: The application of two-level attention models in deep convolutional neural network for fine-grained image classification – year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0240 article-title: Deep structured output learning for unconstrained text recognition – volume: 48 start-page: 2993 issue: 10 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0071 article-title: Deep feature learning with relative distance comparison for person re-identification publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2015.04.005 – start-page: 392 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0052 article-title: Multi-scale orderless pooling of deep convolutional activation features – start-page: 1269 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0137 article-title: Exploiting linear structure within convolutional networks for efficient evaluation – volume: 22 start-page: 986 issue: 8 year: 2003 ident: 10.1016/j.patcog.2017.10.013_bib0187 article-title: Mutual-information-based registration of medical images: a survey publication-title: IEEE Trans. Med. Imaging doi: 10.1109/TMI.2003.815867 – start-page: 1113 year: 2009 ident: 10.1016/j.patcog.2017.10.013_bib0164 article-title: Feature hashing for large scale multitask learning – volume: 64 start-page: 1 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0232 article-title: A comprehensive survey of mostly textual document segmentation algorithms since 2008 publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.10.023 – volume: 44 start-page: 572 issue: 3 year: 2011 ident: 10.1016/j.patcog.2017.10.013_bib0284 article-title: Survey on speech emotion recognition: features, classification schemes, and databases publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2010.09.020 – volume: 48 start-page: 1844 issue: 5 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0195 article-title: A coarse-to-fine approach for fast deformable object detection publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2014.11.006 – start-page: 387 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0236 article-title: Robust seed localization and growing with deep convolutional features for scene text detection – volume: 7 start-page: 669 issue: 4 year: 1993 ident: 10.1016/j.patcog.2017.10.013_bib0064 article-title: Signature verification using a siamese time delay neural network publication-title: Int. J. Pattern Recognit. Artif. Intell. (IJPRAI) doi: 10.1142/S0218001493000339 – start-page: 2351 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0212 article-title: Adaptive object detection using adjacency and zoom prediction – volume: 70 start-page: 60 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0201 article-title: Textproposals: a text-specific selective search algorithm for word spotting in the wild publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2017.04.027 – start-page: 3620 year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0281 article-title: Dag-recurrent neural networks for scene labeling – start-page: 933 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0308 article-title: Language modeling with gated convolutional networks – start-page: 1347 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0227 article-title: Combining local appearance and holistic view: dual-source deep neural networks for human pose estimation – start-page: 4624 year: 2015 ident: 10.1016/j.patcog.2017.10.013_bib0292 article-title: Speech acoustic modeling from raw multichannel waveforms – volume: 61 start-page: 610 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0171 article-title: Facial expression recognition with convolutional neural networks: coping with few data and the training sample order publication-title: Pattern Recognit. doi: 10.1016/j.patcog.2016.07.026 – volume: 13 start-page: 3 issue: 1 year: 1981 ident: 10.1016/j.patcog.2017.10.013_bib0271 article-title: A survey on image segmentation publication-title: Pattern Recognit. doi: 10.1016/0031-3203(81)90028-5 – year: 2016 ident: 10.1016/j.patcog.2017.10.013_bib0038 article-title: Neural machine translation in linear time publication-title: CoRR abs/1610.10099 – start-page: 9 year: 2012 ident: 10.1016/j.patcog.2017.10.013_bib0013 article-title: Efficient backprop – start-page: 1746 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0312 article-title: Convolutional neural networks for sentence classification – start-page: 580 year: 2014 ident: 10.1016/j.patcog.2017.10.013_bib0202 article-title: Rich feature hierarchies for accurate object detection and semantic segmentation – start-page: 588 year: 2013 ident: 10.1016/j.patcog.2017.10.013_bib0260 article-title: Poselet conditioned pictorial structures – volume: 39 start-page: 677 issue: 4 year: 2017 ident: 10.1016/j.patcog.2017.10.013_bib0270 article-title: Long-term recurrent convolutional networks for visual recognition and description publication-title: IEEE Trans. Pattern Anal.Mach.Intell. (PAMI) doi: 10.1109/TPAMI.2016.2599174
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Snippet	•We give an overview of the basic components of CNN.•We discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss...
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SubjectTerms	Convolutional neural network Deep learning
Title	Recent advances in convolutional neural networks
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