Towards Compact 1-bit CNNs via Bayesian Learning

• Published in: International journal of computer vision Vol. 130; no. 2; pp. 201 - 225
• Main Authors: Zhao, Junhe, Xu, Sheng, Zhang, Baochang, Gu, Jiaxin, Doermann, David, Guo, Guodong
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.02.2022; Springer; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Artificial neural networks; Back propagation; Bayesian analysis; Comparative analysis; Computer Imaging; Computer Science; Computer vision; Data mining; Deep learning; Electronic devices; Image Processing and Computer Vision; Kernels; Machine learning; Machine vision; Neural networks; Normal distribution; Object recognition; Pattern Recognition; Pattern Recognition and Graphics; Performance enhancement; Smartphones; Vision; Quantization; Pruning; Binarized network; Bayesian learning

Deep convolutional neural networks (DCNNs) have dominated as the best performers on almost all computer vision tasks over the past several years. However, it remains a major challenge to deploy these powerful DCNNs in resource-limited environments, such as embedded devices and smartphones. To this e...