143 citations · 183 across the 3 of their papers we have counts for
3 papers · 1 filter
Generative adversarial networks and adversarial methods in biomedical image analysis
Jelmer M. Wolterink, Konstantinos Kamnitsas, Christian Ledig +1
Generative adversarial networks (GANs) and other adversarial methods are based on a game-theoretical perspective on joint optimization of two neural networks as players in a game.…
Employing Weak Annotations for Medical Image Analysis Problems
Martin Rajchl, Lisa M. Koch, Christian Ledig +4
To efficiently establish training databases for machine learning methods, collaborative and crowdsourcing platforms have been investigated to collectively tackle the annotation eff…
Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize
Andrew Aitken, Christian Ledig, Lucas Theis +3
The most prominent problem associated with the deconvolution layer is the presence of checkerboard artifacts in output images and dense labels. To combat this problem, smoothness c…