43 citations · 113 across the 17 of their papers we have counts for
4 papers · 1 filter
R3L: Connecting Deep Reinforcement Learning to Recurrent Neural Networks for Image Denoising via Residual Recovery
Rongkai Zhang, Jiang Zhu, Zhiyuan Zha +2
State-of-the-art image denoisers exploit various types of deep neural networks via deterministic training. Alternatively, very recent works utilize deep reinforcement learning for…
The Power of Triply Complementary Priors for Image Compressive Sensing
Zhiyuan Zha, Xin Yuan, Joey Tianyi Zhou +3
Recent works that utilized deep models have achieved superior results in various image restoration applications. Such approach is typically supervised which requires a corpus of tr…
A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems
Bihan Wen, Yanjun Li, Yuqi Li +1
Image prior modeling is the key issue in image recovery, computational imaging, compresses sensing, and other inverse problems. Recent algorithms combining multiple effective prior…
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks
Bihan Wen, Saiprasad Ravishankar, Luke Pfister +1
Magnetic resonance imaging (MRI) is widely used in clinical practice, but it has been traditionally limited by its slow data acquisition. Recent advances in compressed sensing (CS)…