An information-theoretic perspective of physical adversarial patches

Author:

Tarchoun BilelORCID,Ben Khalifa AnouarORCID,Mahjoub Mohamed Ali,Abu-Ghazaleh Nael,Alouani IhsenORCID

Funder

Région Hauts-de-France

Publisher

Elsevier BV

Reference28 articles.

1. Akhtar, N., Liu, J., & Mian, A. (2018). Defense Against Universal Adversarial Perturbations. In Proceedings of the IEEE conference on computer vision and pattern recognition.

2. Fast image inpainting based on coherence transport;Bornemann;Journal of Mathematical Imaging and Vision,2007

3. Brown, T. B., Mané, D., Roy, A., Abadi, M., & Gilmer, J. (2017). Adversarial patch. http://dx.doi.org/10.48550/ARXIV.1712.09665. URL https://arxiv.org/abs/1712.09665.

4. Towards evaluating the robustness of neural networks;Carlini,2017

5. Turning your strength against you: Detecting and mitigating robust and universal adversarial patch attacks;Chen,2021

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