Robust Detection of Directional Adversarial Attacks in Deep Neural Networks for Radiological Imaging
cs.CV, cs.CR, cs.LG
Submitted: 2026-10-11
Updated: 2026-10-11
Terminology
Sources
- Explaining and Harnessing Adversarial Examples
- A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks
- Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
- Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems
- Towards Deep Learning Models Resistant to Adversarial Attacks
- A Tutorial on Adversarial Learning Attacks and Countermeasures
- Evaluating Adversarial Robustness: A Comparison Of FGSM, Carlini-Wagner Attacks, And The Role of Distillation as Defense Mechanism
- Intriguing properties of neural networks
- Fast is better than free: Revisiting adversarial training
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