2020
Detecting Adversarial Samples Using Influence Functions and Nearest Neighbors
CVPR 2020poster
Deep neural networks (DNNs) are notorious for their vulnerability to adversarial attacks, which are small perturbations added to their input images to mislead their prediction. Detection of adversarial examples is, therefore, a fundamental requirement for robust classification frameworks. In this wo…