most citedAccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient

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

collaborators

1 paper

cs.LG2022★ 4 cited

AccelAT: A Framework for Accelerating the Adversarial Training of Deep Neural Networks through Accuracy Gradient

Farzad Nikfam, Alberto Marchisio, Maurizio Martina +1

Adversarial training is exploited to develop a robust Deep Neural Network (DNN) model against the malicious altered data. These attacks may have catastrophic effects on DNN models…