DerMAE: Improving skin lesion classification through conditioned latent diffusion and MAE distillation 事件

DerMAE: Improving skin lesion classification through conditioned latent diffusion and MAE distillation arXiv:2602.19848v2 Announce Type: replace Abstract: Skin lesion classification datasets often suffer from severe class imbalance, with malignant cases significantly underrepresented, leading to biased decision boundaries during deep learning training. We address this challenge using class-conditioned diffusion models to generate synthetic dermatological images, followed by self-supervised MAE