Multi-scale Cross-path Concatenation Residual Network for Poisson denoising. - Yueming Su; Qiusheng Lian; Xiaohua Zhang; Baoshun Shi; Fan Xiaoyu (IET Image Process., 2019)

A deep unrolling network inspired by total variation for compressed sensing MRI. - Xiaohua Zhang; Qiusheng Lian; Yuchi Yang; Yueming Su (Digit. Signal Process., 2020)

iPiano-Net: Nonconvex optimization inspired multi-scale reconstruction network for compressed sensing. - Yueming Su; Qiusheng Lian (Signal Process. Image Commun., 2020)

Supervised dual tight frame learning with deep thresholding network for phase retrieval. - Baoshun Shi; Qiusheng Lian; Yueming Su (IET Image Process., 2022)

LG-Net: Local and global complementary priors induced multi-stage progressive network for compressed sensing. - Qiusheng Lian; Yueming Su; Baoshun Shi; Dan Zhang (Signal Process., 2023)

DeepCDL-PR: Deep unfolded convolutional dictionary learning with weighted ℓ1-norm for phase retrieval. - Baoshun Shi; Yating Gao; Yueming Su; Qiusheng Lian (Digit. Signal Process., 2023)

Dual-Prior Integrated Image Reconstruction for Quanta Image Sensors Using Multi-Agent Consensus Equilibrium. - Dan Zhang; Qiusheng Lian; Yueming Su; Tengfei Ren (IEEE CAA J. Autom. Sinica, 2023)

Bayesian self-supervised learning allying with Transformer powered compressed sensing imaging. - Yueming Su; Yongli Yang; Baoshun Shi; Yuwei Zhang (Digit. Signal Process., 2023)

Transformer based Douglas-Rachford unrolling network for compressed sensing. - Yueming Su; Qiusheng Lian; Dan Zhang; Baoshun Shi (Signal Process. Image Commun., 2024)

Provable deep video denoiser using spatial-temporal information for video snapshot compressive imaging: Algorithm and convergence analysis. - Baoshun Shi; Dan Li; Yuxin Wang; Yueming Su; Qiusheng Lian (Signal Process., 2024)

SAM-guided complementary prior network for compressed sensing MRI. - Yueming Su; Zheng Liu; Baoshun Shi (Digit. Signal Process., 2025)

Unsupervised learning-based deep sparsifying transform network for joint CT metal artifact reduction and super-resolution reconstruction. - Shengnan Yan; Yingshuai Zhao; Baoshun Shi; Yueming Su (Digit. Signal Process., 2025)

Provably bounded prompting prior network for universal compressed sensing magnetic resonance imaging. - Baoshun Shi; Zheng Liu; Kexun Liu; Yueming Su (Knowl. Based Syst., 2025)

High-capacity quantum wireless multi-hop network communication based on hyperentangled Bell states. - Yongli Yang; Yuguang Yang 001; Yueming Su (J. Supercomput., 2025)