4 citations · 5 across the 5 of their papers we have counts for
5 papers
GraVIS: Grouping Augmented Views from Independent Sources for Dermatology Analysis
Hong-Yu Zhou, Chixiang Lu, Liansheng Wang +1
Self-supervised representation learning has been extremely successful in medical image analysis, as it requires no human annotations to provide transferable representations for dow…
PCRLv2: A Unified Visual Information Preservation Framework for Self-supervised Pre-training in Medical Image Analysis
Hong-Yu Zhou, Chixiang Lu, Chaoqi Chen +2
Recent advances in self-supervised learning (SSL) in computer vision are primarily comparative, whose goal is to preserve invariant and discriminative semantics in latent represent…
Preservational Learning Improves Self-supervised Medical Image Models by Reconstructing Diverse Contexts
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +2
Preserving maximal information is one of principles of designing self-supervised learning methodologies. To reach this goal, contrastive learning adopts an implicit way which is co…
ConvNets vs. Transformers: Whose Visual Representations are More Transferable?
Hong-Yu Zhou, Chixiang Lu, Sibei Yang +1
Vision transformers have attracted much attention from computer vision researchers as they are not restricted to the spatial inductive bias of ConvNets. However, although Transform…
Generalized Organ Segmentation by Imitating One-shot Reasoning using Anatomical Correlation
Hong-Yu Zhou, Hualuo Liu, Shilei Cao +5
Learning by imitation is one of the most significant abilities of human beings and plays a vital role in human's computational neural system. In medical image analysis, given sever…