Search Results for author:
Found 2 papers, 2 papers with code
Regularizers for Single-step Adversarial Training
The proposed regularizers mitigate the effect of gradient masking by harnessing on properties that differentiate a robust model from that of a pseudo robust model.
FDA: Feature Disruptive Attack
Though Deep Neural Networks (DNN) show excellent performance across various computer vision tasks, several works show their vulnerability to adversarial samples, i. e., image samples with imperceptible noise engineered to manipulate the network's prediction.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
