41 citations · 65 across the 3 of their papers we have counts for
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eess.IV2020★ 41 cited
On the interplay between physical and content priors in deep learning for computational imaging
Mo Deng, Shuai Li, Iksung Kang +2
Deep learning (DL) has been applied extensively in many computational imaging problems, often leading to superior performance over traditional iterative approaches. However, two im…
eess.IV2019
Learning to Synthesize: Robust Phase Retrieval at Low Photon counts
Mo Deng, Shuai Li, Alexandre Goy +2
The quality of inverse problem solutions obtained through deep learning [Barbastathis et al, 2019] is limited by the nature of the priors learned from examples presented during the…
eess.IV2019★ 1 cited
Low Photon Budget Phase Retrieval with Perceptual Loss Trained Deep Neural Networks
Mo Deng, Alexandre Goy, Shuai Li +2
Deep neural networks (DNNs) are efficient solvers for ill-posed problems and have been shown to outperform classical optimization techniques in several computational imaging proble…