One pixel attack for fooling deep neural networks

One pixel attack for fooling deep neural networks

24 October 2017

Danilo Vasconcellos Vargas

Kouichi Sakurai

Papers citing "One pixel attack for fooling deep neural networks"

19 / 319 papers shown

Title
Structured Adversarial Attack: Towards General Implementation and Better Interpretability Kaidi Xu Sijia Liu Pu Zhao Pin-Yu Chen Huan Zhang Quanfu Fan Deniz Erdogmus Yanzhi Wang X. Lin AAML 29 160 0 05 Aug 2018
On Lipschitz Bounds of General Convolutional Neural Networks Dongmian Zou R. Balan Maneesh Kumar Singh 24 54 0 04 Aug 2018
Vulnerability Analysis of Chest X-Ray Image Classification Against Adversarial Attacks Saeid Asgari Taghanaki A. Das Ghassan Hamarneh MedIm 37 52 0 09 Jul 2018
N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules Shengchao Liu M. F. Demirel Yingyu Liang GNN NAI 13 192 0 24 Jun 2018
Overfitting or perfect fitting? Risk bounds for classification and regression rules that interpolate M. Belkin Daniel J. Hsu P. Mitra AI4CE 39 256 0 13 Jun 2018
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks Jan Svoboda Jonathan Masci Federico Monti M. Bronstein Leonidas J. Guibas AAML GNN 33 41 0 31 May 2018
Why do deep convolutional networks generalize so poorly to small image transformations? Aharon Azulay Yair Weiss 37 557 0 30 May 2018
A Simple Cache Model for Image Recognition Emin Orhan VLM 25 30 0 21 May 2018
Novel Deep Learning Model for Traffic Sign Detection Using Capsule Networks Amara Dinesh Kumar 22 77 0 11 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar A. Madry OOD AAML 40 786 0 30 Apr 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 22 21 0 23 Apr 2018
Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the $L_0$ Norm Wenjie Ruan Min Wu Youcheng Sun Xiaowei Huang Daniel Kroening Marta Kwiatkowska AAML 27 38 0 16 Apr 2018
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang X. Lin AAML 28 37 0 09 Apr 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 17 810 0 02 Feb 2018
Adversarial Texts with Gradient Methods Zhitao Gong Wenlu Wang Yangqiu Song D. Song Wei-Shinn Ku AAML 34 77 0 22 Jan 2018
LaVAN: Localized and Visible Adversarial Noise D. Karmon Daniel Zoran Yoav Goldberg AAML 33 242 0 08 Jan 2018
What do we need to build explainable AI systems for the medical domain? Andreas Holzinger Chris Biemann C. Pattichis D. Kell 28 682 0 28 Dec 2017
Adversarial Patch Tom B. Brown Dandelion Mané Aurko Roy Martín Abadi Justin Gilmer AAML 37 1,090 0 27 Dec 2017
How morphological development can guide evolution Sam Kriegman Nick Cheney Josh Bongard 44 95 0 20 Nov 2017