82 citations · 101 across the 5 of their papers we have counts for
5 papers
Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images
Jun Shi, Yuanming Zhang, Zheng Li +4
Computer-aided diagnosis (CAD) can help pathologists improve diagnostic accuracy together with consistency and repeatability for cancers. However, the CAD models trained with the h…
Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images
Zhiyang Lu, Zheng Li, Jun Wang +2
The thick-slice magnetic resonance (MR) images are often structurally blurred in coronal and sagittal views, which causes harm to diagnosis and image post-processing. Deep learning…
Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected -Net
Zhiyang Lu, Jun Li, Zheng Li +2
Quantitative Susceptibility Mapping (QSM) is a new phase-based technique for quantifying magnetic susceptibility. The existing QSM reconstruction methods generally require complica…
AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte +26
This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Takin…
Lightweight Image Super-Resolution with Adaptive Weighted Learning Network
Chaofeng Wang, Zheng Li, Jun Shi
Deep learning has been successfully applied to the single-image super-resolution (SISR) task with great performance in recent years. However, most convolutional neural network base…