Search Results - "multi-target regression" :: K.UTB vyhledávací portál

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Automated Loudness Growth Prediction From EEG Signals Using Autoencoder and Multi-Target Regression

by Rama Harshita, D., Tiwari, Nitya, Padole, Himanshu, Nataraj, K. S.
Published in IEEE access (2025)

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Journal Article

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Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H2O2 treatment of wastewater

by Yang, Yi, Shan, Chao, Pan, Bingcai
Published in Water research (Oxford) (15.05.2024)

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Region-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis

by Cao, Xiaohuan, Yang, Jianhua, Gao, Yaozong, Wang, Qian, Shen, Dinggang
Published in IEEE transactions on image processing (01.07.2018)

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Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network

by Lin, Zhichao, Gong, Ting, Wang, Kewen, Li, Zhiwei, He, Hongjian, Tong, Qiqi, Yu, Feng, Zhong, Jianhui
Published in Medical physics (Lancaster) (01.07.2019)

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Journal Article

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Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H 2 O 2 treatment of wastewater

by Yang, Yi, Shan, Chao, Pan, Bingcai
Published in Water research (Oxford) (15.05.2024)

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Journal Article

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Machine Learning Approaches for Quantitative Viscoelastic Response (QVisR) Ultrasound

by Richardson, Joseph B., Moore, Christopher J., Anand, Keerthi S., Yokoyama, Keita A., Gallippi, Caterina M.
Published in IEEE International Ultrasonics Symposium (Online) (07.09.2020)

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Conference Proceeding

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Automated prediction of loudness growth curve using EEG signals

by Tiwari, Nitya, Vadyala, Arjun Reddy, Nataraj, K. S.
Published in Proceedings ... Asia-Pacific Signal and Information Processing Association Annual Summit and Conference APSIPA ASC ... (Online) (03.12.2024)

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Conference Proceeding

Automated Loudness Growth Prediction From EEG Signals Using Autoencoder and Multi-Target Regression

Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H2O2 treatment of wastewater

Region-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis

Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network

Machine learning modeling of fluorescence spectral data for prediction of trace organic contaminant removal during UV/H 2 O 2 treatment of wastewater

Machine Learning Approaches for Quantitative Viscoelastic Response (QVisR) Ultrasound

Automated prediction of loudness growth curve using EEG signals

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