Improving the Transferability of Adversarial Examples with New Iteration
Framework and Input Dropout

Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout

3 June 2021

Papers citing "Improving the Transferability of Adversarial Examples with New Iteration Framework and Input Dropout"

10 / 10 papers shown

Title
Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting Junhua Zou Zhisong Pan Junyang Qiu Xin Liu Ting Rui Wei Li 33 67 0 11 Dec 2021
AdvHat: Real-world adversarial attack on ArcFace Face ID system Stepan Alekseevich Komkov Aleksandr Petiushko AAML CVBM 44 284 0 23 Aug 2019
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment Di Jin Zhijing Jin Qiufeng Wang Peter Szolovits SILM AAML 135 1,064 0 27 Jul 2019
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 93 907 0 09 Dec 2018
Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks Siyue Wang Tianlin Li Pu Zhao Wujie Wen David Kaeli S. Chin Xinyu Lin AAML 46 70 0 13 Sep 2018
Audio Adversarial Examples: Targeted Attacks on Speech-to-Text Nicholas Carlini D. Wagner AAML 83 1,076 0 05 Jan 2018
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 183 8,513 0 16 Aug 2016
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning Christian Szegedy Sergey Ioffe Vincent Vanhoucke Alexander A. Alemi 320 14,196 0 23 Feb 2016
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 357 9,418 0 28 May 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 204 14,831 1 21 Dec 2013