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cs.CV2025
Defending Against Frequency-Based Attacks with Diffusion Models
Fatemeh Amerehi, Patrick Healy
Adversarial training is a common strategy for enhancing model robustness against adversarial attacks. However, it is typically tailored to the specific attack types it is trained o…
cs.CV2025
Narrowing Class-Wise Robustness Gaps in Adversarial Training
Fatemeh Amerehi, Patrick Healy
Efforts to address declining accuracy as a result of data shifts often involve various data-augmentation strategies. Adversarial training is one such method, designed to improve ro…
cs.CV2024
Label Augmentation for Neural Networks Robustness
Fatemeh Amerehi, Patrick Healy
Out-of-distribution generalization can be categorized into two types: common perturbations arising from natural variations in the real world and adversarial perturbations that are…