3 papers
cs.CV2019
Optimal Transport driven CycleGAN for Unsupervised Learning in Inverse Problems
Byeongsu Sim, Gyutaek Oh, Jeongsol Kim +2
To improve the performance of classical generative adversarial network (GAN), Wasserstein generative adversarial networks (W-GAN) was developed as a Kantorovich dual formulation of…
eess.IV2019
CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry
Sungjun Lim, Hyoungjun Park, Sang-Eun Lee +2
Deconvolution microscopy has been extensively used to improve the resolution of the wide-field fluorescent microscopy, but the performance of classical approaches critically depend…
cs.LG2019
Blind Deconvolution Microscopy Using Cycle Consistent CNN with Explicit PSF Layer
Sungjun Lim, Sang-Eun Lee, Sunghoe Chang +1
Deconvolution microscopy has been extensively used to improve the resolution of the widefield fluorescent microscopy. Conventional approaches, which usually require the point sprea…