2 papers
cs.CV2026
Adversarial Wear and Tear: Exploiting Natural Damage for Generating Physical-World Adversarial Examples
Samra Irshad, Seungkyu Lee, Nassir Navab +2
The presence of adversarial examples in the physical world poses significant challenges to the deployment of Deep Neural Networks in safety-critical applications such as autonomous…
cs.LG2025
Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability
Soyoun Won, Sung-Ho Bae, Seong Tae Kim
Mixed sample data augmentation strategies are actively used when training deep neural networks (DNNs). Recent studies suggest that they are effective at various tasks. However, the…