Tal Grinshpoun

Heat and Blur: An Effective and Fast Defense Against Adversarial Examples

2020 · arXiv (Cornell University)

The growing incorporation of artificial neural networks (NNs) into many fields, and especially into life-critical systems, is restrained by their vulnerability to adversarial examples (AEs). Some existing defense methods can increase NNs' robustness, but they …