most citedInterpretations Cannot Be Trusted: Stealthy and Effective Adversarial Perturbations against Interpretable Deep Learning

4 citations · 4 across the 1 of their papers we have counts for

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1 paper

cs.CR2022★ 4 cited

Interpretations Cannot Be Trusted: Stealthy and Effective Adversarial Perturbations against Interpretable Deep Learning

Eldor Abdukhamidov, Mohammed Abuhamad, Simon S. Woo +2

Deep learning methods have gained increased attention in various applications due to their outstanding performance. For exploring how this high performance relates to the proper us…