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1412.5068
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Towards Deep Neural Network Architectures Robust to Adversarial Examples
International Conference on Learning Representations (ICLR), 2014
11 December 2014
S. Gu
Luca Rigazio
AAML
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Papers citing
"Towards Deep Neural Network Architectures Robust to Adversarial Examples"
50 / 417 papers shown
Neuron with Steady Response Leads to Better Generalization
Qiang Fu
Lun Du
Haitao Mao
Xu Chen
Wei Fang
Shi Han
Dongmei Zhang
178
5
0
30 Nov 2021
Using a GAN to Generate Adversarial Examples to Facial Image Recognition
Andrew Merrigan
Alan F. Smeaton
PICV
GAN
80
5
0
30 Nov 2021
Do Invariances in Deep Neural Networks Align with Human Perception?
Vedant Nanda
Ayan Majumdar
Camila Kolling
John P. Dickerson
Krishna P. Gummadi
Bradley C. Love
Adrian Weller
AAML
220
6
0
29 Nov 2021
Enhanced countering adversarial attacks via input denoising and feature restoring
Yanni Li
Wenhui Zhang
Jiawei Liu
Xiaoli Kou
Hui Li
Jiangtao Cui
AAML
160
3
0
19 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps
Neural Information Processing Systems (NeurIPS), 2021
Muhammad Awais
Fengwei Zhou
Chuanlong Xie
Jiawei Li
Sung-Ho Bae
Zhenguo Li
AAML
204
20
0
09 Nov 2021
Generative Dynamic Patch Attack
Xiang Li
Shihao Ji
AAML
235
29
0
08 Nov 2021
Fast Gradient Non-sign Methods
Yaya Cheng
Jingkuan Song
Xiaosu Zhu
Qilong Zhang
Lianli Gao
Heng Tao Shen
AAML
264
12
0
25 Oct 2021
Robust lEarned Shrinkage-Thresholding (REST): Robust unrolling for sparse recover
Wei Pu
Chao Zhou
Yonina C. Eldar
M. Rodrigues
OOD
206
2
0
20 Oct 2021
Trustworthy AI: From Principles to Practices
Yue Liu
Peng Qi
Bo Liu
Shuai Di
Jingen Liu
Jiquan Pei
Jinfeng Yi
Bowen Zhou
473
523
0
04 Oct 2021
Morphence: Moving Target Defense Against Adversarial Examples
Asia-Pacific Computer Systems Architecture Conference (ACSA), 2021
Abderrahmen Amich
Birhanu Eshete
AAML
254
28
0
31 Aug 2021
Physical Adversarial Attacks on an Aerial Imagery Object Detector
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Andrew Du
Bo Chen
Tat-Jun Chin
Yee Wei Law
Michele Sasdelli
Ramesh Rajasegaran
Dillon Campbell
AAML
314
80
0
26 Aug 2021
Optical Adversarial Attack
Abhiram Gnanasambandam
A. Sherman
Stanley H. Chan
AAML
282
79
0
13 Aug 2021
Detect and Defense Against Adversarial Examples in Deep Learning using Natural Scene Statistics and Adaptive Denoising
Anouar Kherchouche
Sid Ahmed Fezza
W. Hamidouche
AAML
164
11
0
12 Jul 2021
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective
Lina Wang
Xingshu Chen
Yulong Wang
Yawei Yue
Yi Zhu
Xuemei Zeng
Wei Wang
AAML
114
0
0
18 Jun 2021
BO-DBA: Query-Efficient Decision-Based Adversarial Attacks via Bayesian Optimization
Zhuosheng Zhang
Shucheng Yu
AAML
136
2
0
04 Jun 2021
Physical world assistive signals for deep neural network classifiers -- neither defense nor attack
Camilo Pestana
Wei Liu
D. Glance
R. Owens
Lin Wang
AAML
90
0
0
03 May 2021
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
Artificial Intelligence Review (AIR), 2021
Ahmed Aldahdooh
W. Hamidouche
Sid Ahmed Fezza
Olivier Déforges
AAML
697
161
0
01 May 2021
Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting
ACM Multimedia (ACM MM), 2021
Qiming Wu
Zhikang Zou
Pan Zhou
Xiaoqing Ye
Binghui Wang
Ang Li
AAML
259
7
0
22 Apr 2021
Removing Adversarial Noise in Class Activation Feature Space
IEEE International Conference on Computer Vision (ICCV), 2021
Dawei Zhou
N. Wang
Chunlei Peng
Xinbo Gao
Xiaoyu Wang
Jun Yu
Tongliang Liu
AAML
149
35
0
19 Apr 2021
ExAD: An Ensemble Approach for Explanation-based Adversarial Detection
R. Vardhan
Ninghao Liu
Phakpoom Chinprutthiwong
Weijie Fu
Zhen Hu
Helen Zhou
G. Gu
AAML
209
5
0
22 Mar 2021
Attribution of Gradient Based Adversarial Attacks for Reverse Engineering of Deceptions
Media Watermarking, Security, and Forensics (MWSF), 2021
Michael Goebel
Jason Bunk
Srinjoy Chattopadhyay
L. Nataraj
S. Chandrasekaran
B. S. Manjunath
AAML
118
4
0
19 Mar 2021
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models
European Symposium on Security and Privacy (EuroS&P), 2021
Benjamin Zi Hao Zhao
Aviral Agrawal
Catisha Coburn
Hassan Jameel Asghar
Raghav Bhaskar
M. Kâafar
Darren Webb
Peter Dickinson
MIACV
125
50
0
12 Mar 2021
Stochastic-HMDs: Adversarial Resilient Hardware Malware Detectors through Voltage Over-scaling
Md. Shohidul Islam
Ihsen Alouani
Khaled N. Khasawneh
AAML
115
1
0
11 Mar 2021
DAFAR: Defending against Adversaries by Feedback-Autoencoder Reconstruction
Haowen Liu
Ping Yi
Hsiao-Ying Lin
Jie Shi
Weidong Qiu
AAML
124
2
0
11 Mar 2021
Improving Adversarial Robustness via Channel-wise Activation Suppressing
International Conference on Learning Representations (ICLR), 2021
Yang Bai
Yuyuan Zeng
Yong Jiang
Shutao Xia
Jiabo He
Yisen Wang
AAML
188
143
0
11 Mar 2021
Revisiting Model's Uncertainty and Confidences for Adversarial Example Detection
Ahmed Aldahdooh
W. Hamidouche
Olivier Déforges
AAML
276
34
0
09 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN
Desheng Wang
Wei-dong Jin
Yunpu Wu
Aamir Khan
GAN
187
10
0
08 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack
Mengting Xu
Tao Zhang
Zhongnian Li
Mingxia Liu
Daoqiang Zhang
AAML
OOD
MedIm
177
51
0
05 Mar 2021
Brain Programming is Immune to Adversarial Attacks: Towards Accurate and Robust Image Classification using Symbolic Learning
Swarm and Evolutionary Computation (Swarm Evol. Comput.), 2021
Gerardo Ibarra-Vázquez
Gustavo Olague
Mariana Chan-Ley
Cesar Puente
C. Soubervielle-Montalvo
AAML
142
16
0
01 Mar 2021
Adversarial Information Bottleneck
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
Penglong Zhai
Shihua Zhang
AAML
175
14
0
28 Feb 2021
Towards Causal Representation Learning
Bernhard Schölkopf
Francesco Locatello
Stefan Bauer
Nan Rosemary Ke
Nal Kalchbrenner
Anirudh Goyal
Yoshua Bengio
OOD
CML
AI4CE
346
342
0
22 Feb 2021
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids
International Conference on Computer Communications and Networks (ICCCN), 2021
Jiangnan Li
Yingyuan Yang
Jinyuan Stella Sun
K. Tomsovic
Hairong Qi
AAML
269
20
0
17 Feb 2021
Security and Privacy for Artificial Intelligence: Opportunities and Challenges
Ayodeji Oseni
Nour Moustafa
Helge Janicke
Peng Liu
Z. Tari
A. Vasilakos
AAML
166
65
0
09 Feb 2021
SPADE: A Spectral Method for Black-Box Adversarial Robustness Evaluation
International Conference on Machine Learning (ICML), 2021
Wuxinlin Cheng
Chenhui Deng
Zhiqiang Zhao
Yaohui Cai
Zhiru Zhang
Zhuo Feng
AAML
305
20
0
07 Feb 2021
Adversarial Attacks and Defenses in Physiological Computing: A Systematic Review
National Science Open (NSO), 2021
Dongrui Wu
Jiaxin Xu
Weili Fang
Yi Zhang
Liuqing Yang
Xiaodong Xu
Hanbin Luo
Xiang Yu
AAML
391
28
0
04 Feb 2021
Key Technology Considerations in Developing and Deploying Machine Learning Models in Clinical Radiology Practice
JMIR Medical Informatics (JMIR Med Inform), 2021
V. Kulkarni
M. Gawali
A. Kharat
VLM
259
27
0
03 Feb 2021
Towards Speeding up Adversarial Training in Latent Spaces
Yaguan Qian
Qiqi Shao
Tengteng Yao
Bin Wang
R. Beyah
Shaoning Zeng
Zhaoquan Gu
Wassim Swaileh
AAML
120
5
0
01 Feb 2021
Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021
F. Nesti
Alessandro Biondi
Giorgio Buttazzo
AAML
125
50
0
27 Jan 2021
Online Adversarial Purification based on Self-Supervision
International Conference on Learning Representations (ICLR), 2021
Changhao Shi
Chester Holtz
Zhengchao Wan
AAML
181
61
0
23 Jan 2021
Adaptive Neighbourhoods for the Discovery of Adversarial Examples
Jay Morgan
A. Paiement
A. Pauly
Monika Seisenberger
AAML
114
1
0
22 Jan 2021
On the Effectiveness of Small Input Noise for Defending Against Query-based Black-Box Attacks
IEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2021
Junyoung Byun
Hyojun Go
Changick Kim
AAML
332
24
0
13 Jan 2021
Understanding the Error in Evaluating Adversarial Robustness
Pengfei Xia
Wandi Qiao
Hongjing Niu
Bin Li
AAML
ELM
165
5
0
07 Jan 2021
On the Limitations of Denoising Strategies as Adversarial Defenses
Zhonghan Niu
Zhaoxi Chen
Linyi Li
Yubin Yang
Yue Liu
Jinfeng Yi
AAML
159
14
0
17 Dec 2020
Mitigating the Impact of Adversarial Attacks in Very Deep Networks
Mohammed Hassanin
Ibrahim Radwan
Nour Moustafa
M. Tahtali
Neeraj Kumar
AAML
154
7
0
08 Dec 2020
Learning to Separate Clusters of Adversarial Representations for Robust Adversarial Detection
Byunggill Joe
Jihun Hamm
Sung Ju Hwang
Sooel Son
I. Shin
AAML
OOD
212
0
0
07 Dec 2020
FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques
Han Qiu
Yi Zeng
Tianwei Zhang
Yong Jiang
Meikang Qiu
AAML
139
15
0
03 Dec 2020
A Black-Box Attack Model for Visually-Aware Recommender Systems
Rami Cohen
Oren Sar Shalom
Dietmar Jannach
A. Amir
138
31
0
05 Nov 2020
The Vulnerability of the Neural Networks Against Adversarial Examples in Deep Learning Algorithms
Rui Zhao
AAML
140
1
0
02 Nov 2020
LG-GAN: Label Guided Adversarial Network for Flexible Targeted Attack of Point Cloud-based Deep Networks
Computer Vision and Pattern Recognition (CVPR), 2020
Hang Zhou
Dongdong Chen
Jing Liao
Weiming Zhang
Kejiang Chen
Xiaoyi Dong
Kunlin Liu
G. Hua
Nenghai Yu
3DPC
226
121
0
01 Nov 2020
Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable?
International Conference on Machine Learning (ICML), 2020
Anna-Kathrin Kopetzki
Bertrand Charpentier
Daniel Zügner
Sandhya Giri
Stephan Günnemann
321
53
0
28 Oct 2020
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