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cs.CV2026
Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning
Jiahe Chen, Qian Shao, Qiyuan Chen +4
Open-set semi-supervised learning aims to leverage unlabeled data that may contain out-of-distribution outliers while maintaining performance on in-distribution classes. Existing m…
cs.CV2025
C3S3: Complementary Competition and Contrastive Selection for Semi-Supervised Medical Image Segmentation
Jiaying He, Yitong Lin, Jiahe Chen +2
For the immanent challenge of insufficiently annotated samples in the medical field, semi-supervised medical image segmentation (SSMIS) offers a promising solution. Despite achievi…
cs.CV2025
Decoupled Competitive Framework for Semi-supervised Medical Image Segmentation
Jiahe Chen, Jiahe Ying, Shen Wang +1
Confronting the critical challenge of insufficiently annotated samples in medical domain, semi-supervised medical image segmentation (SSMIS) emerges as a promising solution. Specif…