4 papers
Patch-Wise Hypergraph Contrastive Learning with Dual Normal Distribution Weighting for Multi-Domain Stain Transfer
Haiyan Wei, Hangrui Xu, Bingxu Zhu +4
Virtual stain transfer leverages computer-assisted technology to transform the histochemical staining patterns of tissue samples into other staining types. However, existing method…
The Power of Many: Synergistic Unification of Diverse Augmentations for Efficient Adversarial Robustness
Wang Yu-Hang, Shiwei Li, Jianxiang Liao +3
Adversarial perturbations pose a significant threat to deep learning models. Adversarial Training (AT), the predominant defense method, faces challenges of high computational costs…
Ignition Phase : Standard Training for Fast Adversarial Robustness
Wang Yu-Hang, Liu ying, Fang liang +6
Adversarial Training (AT) is a cornerstone defense, but many variants overlook foundational feature representations by primarily focusing on stronger attack generation. We introduc…
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions
Wang YuHang, Junkang Guo, Aolei Liu +5
Adversarial robustness is a critical challenge in deploying deep neural networks for real-world applications. While adversarial training is a widely recognized defense strategy, mo…