5 citations · 6 across the 4 of their papers we have counts for
4 papers
Bi-Level Collaborative Learning for Few-Shot Scribble-Supervised Medical Image Segmentation
Xiang-Xiang Su, Yufan Ye, Yihang Zheng +2
Scribble annotations offer an efficient alternative to costly pixel-wise labeling for medical image segmentation, yet in real clinical scenarios, scribble-annotated samples are oft…
High-Similarity-Pass Attention for Single Image Super-Resolution
Jian-Nan Su, Min Gan, Guang-Yong Chen +2
Recent developments in the field of non-local attention (NLA) have led to a renewed interest in self-similarity-based single image super-resolution (SISR). Researchers usually used…
Online Learning Under A Separable Stochastic Approximation Framework
Min Gan, Xiang-xiang Su, Guang-yong Chen +1
We propose an online learning algorithm for a class of machine learning models under a separable stochastic approximation framework. The essence of our idea lies in the observation…
Global Learnable Attention for Single Image Super-Resolution
Jian-Nan Su, Min Gan, Guang-Yong Chen +2
Self-similarity is valuable to the exploration of non-local textures in single image super-resolution (SISR). Researchers usually assume that the importance of non-local textures i…