IEEE

Rectifying Adversarial Examples Using Their Vulnerabilities

Abstract: Deep neural network-based classifiers are prone to errors when processing adversarial examples (AEs). AEs are minimally perturbed input data undetectable to humans posing significant risks ...
IEEE

Adversarial Example Generation With Pseudo-Siamese Adversarial Generative Networks for Multimodal Remote Sensing Images

Abstract: In the field of remote sensing, the increasing diversity of remote sensing image modalities has made the integration of multimodal remote sensing image information a prevailing trend to ...