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cs.CV2024
Distilling Adversarial Robustness Using Heterogeneous Teachers
Jieren Deng, Aaron Palmer, Rigel Mahmood +4
Achieving resiliency against adversarial attacks is necessary prior to deploying neural network classifiers in domains where misclassification incurs substantial costs, e.g., self-…
cs.CV2021★ 1 cited
On the Robustness of Vision Transformers to Adversarial Examples
Kaleel Mahmood, Rigel Mahmood, Marten van Dijk
Recent advances in attention-based networks have shown that Vision Transformers can achieve state-of-the-art or near state-of-the-art results on many image classification tasks. Th…