Dynamic Perturbation-Adaptive Adversarial Training on Medical Image
Classification
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image
Classification
Remarkable successes were made in Medical Image Classification (MIC) recently, mainly due to wide applications of convolutional neural networks (CNNs). However, adversarial examples (AEs) exhibited imperceptible similarity with raw data, raising serious concerns on network robustness. Although adversarial training (AT), in responding to malevolent AEs, was recognized as an effective …