13 citations · 37 across the 13 of their papers we have counts for
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Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +3
Background and objective: High-resolution radiographic images play a pivotal role in the early diagnosis and treatment of skeletal muscle-related diseases. It is promising to enhan…
Infrared Image Super-Resolution via GAN
Yongsong Huang, Shinichiro Omachi
The ability of generative models to accurately fit data distributions has resulted in their widespread adoption and success in fields such as computer vision and natural language p…
Texture and Noise Dual Adaptation for Infrared Image Super-Resolution
Yongsong Huang, Tomo Miyazaki, Xiaofeng Liu +2
Recent efforts have explored leveraging visible light images to enrich texture details in infrared (IR) super-resolution. However, this direct adaptation approach often becomes a d…
Vicinal Feature Statistics Augmentation for Federated 3D Medical Volume Segmentation
Yongsong Huang, Wanqing Xie, Mingzhen Li +5
Federated learning (FL) enables multiple client medical institutes collaboratively train a deep learning (DL) model with privacy protection. However, the performance of FL can be c…