2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CV2022
Wavelet Regularization Benefits Adversarial Training
Jun Yan, Huilin Yin, Xiaoyang Deng +4
Adversarial training methods are state-of-the-art (SOTA) empirical defense methods against adversarial examples. Many regularization methods have been proven to be effective with t…
cs.LG2021★ 2 cited
On Procedural Adversarial Noise Attack And Defense
Jun Yan, Xiaoyang Deng, Huilin Yin +1
Deep Neural Networks (DNNs) are vulnerable to adversarial examples which would inveigle neural networks to make prediction errors with small perturbations on the input images. Rese…