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An Assessment of Robustness for Adversarial Attacks and Physical Distortions on Image Classification using Explainable AI
2021
SGAI Conferences
Introducing defence mechanisms to overcome the vulnerability of adversarial attacks is a highly focused research area. However recent research highlights that introducing defence approaches for man-made adversarial attacks is not sufficient, because the deep learning models are vulnerable to the perturbations outside the scope of the training set and the physical world itself acts as an adversarial sample generator. Given this caveat, there is a necessity to introduce general defence approaches
dblp:conf/sgai/MahimaAP21
fatcat:rdwwpu3eufcujarr4m7uh2a7ty