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Zehan Wang
Zehan Wang
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Year
Photo-realistic single image super-resolution using a generative adversarial network
C Ledig, L Theis, F Huszár, J Caballero, A Cunningham, A Acosta, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2017
124032017
Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
W Shi, J Caballero, F Huszár, J Totz, AP Aitken, R Bishop, D Rueckert, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2016
65072016
Real-time video super-resolution with spatio-temporal networks and motion compensation
J Caballero, C Ledig, A Aitken, A Acosta, J Totz, Z Wang, W Shi
Proceedings of the IEEE conference on computer vision and pattern …, 2017
7672017
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Institute of Electrical and Electronics Engineers
IEEE, 2019
5052019
Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize
A Aitken, C Ledig, L Theis, J Caballero, Z Wang, W Shi
arXiv preprint arXiv:1707.02937, 2017
1842017
Is the deconvolution layer the same as a convolutional layer?
W Shi, J Caballero, L Theis, F Huszar, A Aitken, C Ledig, Z Wang
arXiv preprint arXiv:1609.07009, 2016
1762016
Discriminative dictionary learning for abdominal multi-organ segmentation
T Tong, R Wolz, Z Wang, Q Gao, K Misawa, M Fujiwara, K Mori, JV Hajnal, ...
Medical image analysis 23 (1), 92-104, 2015
1592015
Super resolution using a generative adversarial network
W Shi, C Ledig, Z Wang, L Theis, F Huszar
US Patent 11,024,009, 2021
1402021
Enhancing visual data using and augmenting model libraries
Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz
US Patent 10,499,069, 2019
972019
Training end-to-end video processes
Z Wang, RD Bishop, F Huszar, L Theis
US Patent 10,681,361, 2020
902020
Geodesic Patch-based Segmentation
Z Wang, K Bhatia, B Glocker, A de Marvao, T Dawes, K Misawa, K Mori, ...
842014
Photo-realistic single image super-resolution using a generative adversarial network. arXiv 2016
C Ledig, L Theis, F Huszar, J Caballero, A Cunningham, A Acosta, ...
arXiv preprint arXiv:1609.04802, 2016
662016
Machine learning for visual processing
Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz
US Patent 11,528,492, 2022
642022
Frame interpolation with multi-scale deep loss functions and generative adversarial networks
J Van Amersfoort, W Shi, A Acosta, F Massa, J Totz, Z Wang, J Caballero
arXiv preprint arXiv:1711.06045, 2017
482017
Real-time video super-resolution with spatio-temporal networks and motion compensation
J Caballero, C Ledig, A Aitken, AAA Diaz, L Theis, F Huszar, J Totz, ...
US Patent 10,701,394, 2020
362020
Training end-to-end video processes
Z Wang, RD Bishop, F Huszar, L Theis
US Patent 10,666,962, 2020
362020
Online Training of Hierarchical Algorithms
Z Wang, RD Bishop, W Shi, J Caballero, AP Aitken, J Totz
US Patent App. 15/679,660, 2017
342017
Patch-based segmentation without registration: application to knee MRI
Z Wang, C Donoghue, D Rueckert
Machine Learning in Medical Imaging: 4th International Workshop, MLMI 2013 …, 2013
342013
Generative methods of super resolution
Z Wang, W Shi, F Huszar, RD Bishop
US Patent 10,692,185, 2020
302020
Active learning system
F Huszar, P Berkes, Z Wang
US Patent App. 15/876,906, 2018
272018
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