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Deep Neural Networks are Easily Fooled: High Confidence Predictions for
  Unrecognizable Images
v1v2v3v4 (latest)

Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images

Computer Vision and Pattern Recognition (CVPR), 2014
5 December 2014
Anh Totti Nguyen
J. Yosinski
Jeff Clune
    AAML
ArXiv (abs)PDFHTML

Papers citing "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images"

50 / 1,455 papers shown
Perceptual Attention-based Predictive Control
Perceptual Attention-based Predictive Control
Keuntaek Lee
G. N. An
Viacheslav Zakharov
Evangelos A. Theodorou
168
20
0
26 Apr 2019
The Scientific Method in the Science of Machine Learning
The Scientific Method in the Science of Machine Learning
Jessica Zosa Forde
Michela Paganini
140
40
0
24 Apr 2019
Optimization and Abstraction: A Synergistic Approach for Analyzing
  Neural Network Robustness
Optimization and Abstraction: A Synergistic Approach for Analyzing Neural Network Robustness
Greg Anderson
Shankara Pailoor
Işıl Dillig
Swarat Chaudhuri
AAML
227
103
0
22 Apr 2019
Deep Anchored Convolutional Neural Networks
Deep Anchored Convolutional Neural Networks
Jiahui Huang
Kshitij Dwivedi
Gemma Roig
108
1
0
22 Apr 2019
GAN-based Generation and Automatic Selection of Explanations for Neural
  Networks
GAN-based Generation and Automatic Selection of Explanations for Neural Networks
Saumitra Mishra
Daniel Stoller
Emmanouil Benetos
Bob L. T. Sturm
Simon Dixon
AAML
106
12
0
21 Apr 2019
Fashion++: Minimal Edits for Outfit Improvement
Fashion++: Minimal Edits for Outfit Improvement
Wei-Lin Hsiao
Isay Katsman
Chao-Yuan Wu
Devi Parikh
Kristen Grauman
302
71
0
19 Apr 2019
Understanding Neural Networks via Feature Visualization: A survey
Understanding Neural Networks via Feature Visualization: A survey
Anh Nguyen
J. Yosinski
Jeff Clune
FAtt
200
173
0
18 Apr 2019
Adversarial Defense Through Network Profiling Based Path Extraction
Adversarial Defense Through Network Profiling Based Path Extraction
Yuxian Qiu
Jingwen Leng
Cong Guo
Quan Chen
Chong Li
Minyi Guo
Yuhao Zhu
AAML
112
56
0
17 Apr 2019
AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial
  Examples
AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial Examples
Xiaosen Wang
Kun He
Chuanbiao Song
Liwei Wang
John E. Hopcroft
GAN
120
39
0
16 Apr 2019
Generating Minimal Adversarial Perturbations with Integrated Adaptive Gradients
Yatie Xiao
Chi-Man Pun
AAMLGANTTA
38
0
0
12 Apr 2019
Black-Box Decision based Adversarial Attack with Symmetric
  $α$-stable Distribution
Black-Box Decision based Adversarial Attack with Symmetric ααα-stable Distribution
Vignesh Srinivasan
E. Kuruoglu
K. Müller
Wojciech Samek
Shinichi Nakajima
AAML
130
7
0
11 Apr 2019
Black-box Adversarial Attacks on Video Recognition Models
Black-box Adversarial Attacks on Video Recognition Models
Linxi Jiang
Jiabo He
Shaoxiang Chen
James Bailey
Yu-Gang Jiang
AAMLMLAU
227
160
0
10 Apr 2019
A Target-Agnostic Attack on Deep Models: Exploiting Security
  Vulnerabilities of Transfer Learning
A Target-Agnostic Attack on Deep Models: Exploiting Security Vulnerabilities of Transfer Learning
Shahbaz Rezaei
Xin Liu
SILMAAML
283
47
0
08 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and
  Suppression
Interpreting Adversarial Examples by Activation Promotion and Suppression
Kaidi Xu
Sijia Liu
Gaoyuan Zhang
Mengshu Sun
Pu Zhao
Quanfu Fan
Chuang Gan
Xinyu Lin
AAMLFAtt
292
46
0
03 Apr 2019
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
Finding and Visualizing Weaknesses of Deep Reinforcement Learning Agents
Christian Rupprecht
Cyril Ibrahim
C. Pal
171
34
0
02 Apr 2019
On the Adversarial Robustness of Multivariate Robust Estimation
On the Adversarial Robustness of Multivariate Robust Estimation
Erhan Bayraktar
Lifeng Lai
86
3
0
27 Mar 2019
Interpreting Neural Networks Using Flip Points
Interpreting Neural Networks Using Flip Points
Roozbeh Yousefzadeh
D. O’Leary
AAMLFAtt
124
18
0
21 Mar 2019
On the Robustness of Deep K-Nearest Neighbors
On the Robustness of Deep K-Nearest Neighbors
Chawin Sitawarin
David Wagner
AAMLOOD
178
62
0
20 Mar 2019
Practical Hidden Voice Attacks against Speech and Speaker Recognition
  Systems
Practical Hidden Voice Attacks against Speech and Speaker Recognition SystemsNetwork and Distributed System Security Symposium (NDSS), 2019
H. Abdullah
Washington Garcia
Christian Peeters
Patrick Traynor
Kevin R. B. Butler
Joseph N. Wilson
AAML
155
178
0
18 Mar 2019
Aesthetics of Neural Network Art
Aesthetics of Neural Network Art
Aaron Hertzmann
GAN
52
16
0
13 Mar 2019
Alignment Based Matching Networks for One-Shot Classification and
  Open-Set Recognition
Alignment Based Matching Networks for One-Shot Classification and Open-Set Recognition
Paresh Malalur
Tommi Jaakkola
ObjDVLM
83
0
0
11 Mar 2019
Learning from Higher-Layer Feature Visualizations
Learning from Higher-Layer Feature Visualizations
K. Nikolaidis
Stein Kristiansen
V. Goebel
T. Plagemann
108
5
0
06 Mar 2019
Deep Learning for Cognitive Neuroscience
Deep Learning for Cognitive Neuroscience
Katherine R. Storrs
N. Kriegeskorte
NAIAI4CE
161
48
0
04 Mar 2019
Evaluating Adversarial Evasion Attacks in the Context of Wireless
  Communications
Evaluating Adversarial Evasion Attacks in the Context of Wireless CommunicationsIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2019
Bryse Flowers
R. M. Buehrer
William C. Headley
AAML
183
150
0
01 Mar 2019
TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents
TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents
Panagiota Kiourti
Kacper Wardega
Susmit Jha
Wenchao Li
AAML
109
57
0
01 Mar 2019
Towards Understanding Adversarial Examples Systematically: Exploring
  Data Size, Task and Model Factors
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors
Ke Sun
Zhanxing Zhu
Zhouchen Lin
AAML
146
19
0
28 Feb 2019
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher
  Precision and Faster Verification
Analyzing Deep Neural Networks with Symbolic Propagation: Towards Higher Precision and Faster VerificationSensors Applications Symposium (SAS), 2019
Jianlin Li
Pengfei Yang
Jiangchao Liu
Liqian Chen
Xiaowei Huang
Lijun Zhang
AAML
177
83
0
26 Feb 2019
Adversarial Reinforcement Learning under Partial Observability in
  Autonomous Computer Network Defence
Adversarial Reinforcement Learning under Partial Observability in Autonomous Computer Network Defence
Yi Han
David Hubczenko
Paul Montague
O. Vel
Tamas Abraham
Benjamin I. P. Rubinstein
C. Leckie
T. Alpcan
S. Erfani
AAML
226
6
0
25 Feb 2019
DeepFault: Fault Localization for Deep Neural Networks
DeepFault: Fault Localization for Deep Neural Networks
Hasan Ferit Eniser
Simos Gerasimou
A. Sen
AAML
140
95
0
15 Feb 2019
Can Intelligent Hyperparameter Selection Improve Resistance to
  Adversarial Examples?
Can Intelligent Hyperparameter Selection Improve Resistance to Adversarial Examples?
Cody Burkard
Brent Lagesse
AAMLSILM
81
1
0
14 Feb 2019
Deep Divergence-Based Approach to Clustering
Deep Divergence-Based Approach to ClusteringNeural Networks (NN), 2019
Michael C. Kampffmeyer
Sigurd Løkse
F. Bianchi
L. Livi
Arnt-Børre Salberg
Robert Jenssen
205
72
0
13 Feb 2019
Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving
Yes, we GAN: Applying Adversarial Techniques for Autonomous Driving
Michal Uřičář
P. Krízek
David Hurych
Ibrahim Sobh
S. Yogamani
Patrick Denny
GAN
261
59
0
09 Feb 2019
Image Decomposition and Classification through a Generative Model
Image Decomposition and Classification through a Generative ModelInternational Conference on Information Photonics (ICIP), 2019
Houpu Yao
Malcolm Regan
Yezhou Yang
Yi Ren
GAN
89
1
0
09 Feb 2019
Understanding the One-Pixel Attack: Propagation Maps and Locality
  Analysis
Understanding the One-Pixel Attack: Propagation Maps and Locality Analysis
Danilo Vasconcellos Vargas
Jiawei Su
FAttAAML
107
39
0
08 Feb 2019
Situational Grounding within Multimodal Simulations
Situational Grounding within Multimodal Simulations
James Pustejovsky
Nikhil Krishnaswamy
LM&Ro
86
8
0
05 Feb 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of
  Key Ideas and Publications, and Bibliography for Explainable AI
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI
Shane T. Mueller
R. Hoffman
W. Clancey
Abigail Emrey
Gary Klein
XAI
258
307
0
05 Feb 2019
Adaptive Gradient for Adversarial Perturbations Generation
Yatie Xiao
Chi-Man Pun
ODL
173
10
0
01 Feb 2019
Natural and Adversarial Error Detection using Invariance to Image
  Transformations
Natural and Adversarial Error Detection using Invariance to Image Transformations
Yuval Bahat
Michal Irani
Gregory Shakhnarovich
AAML
179
20
0
01 Feb 2019
Optimal Attack against Autoregressive Models by Manipulating the
  Environment
Optimal Attack against Autoregressive Models by Manipulating the EnvironmentAAAI Conference on Artificial Intelligence (AAAI), 2019
Yiding Chen
Xiaojin Zhu
AAML
164
11
0
01 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial
  Attacks
A New Family of Neural Networks Provably Resistant to Adversarial Attacks
Rakshit Agrawal
Luca de Alfaro
D. Helmbold
AAMLOOD
59
2
0
01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks
Augmenting Model Robustness with Transformation-Invariant Attacks
Houpu Yao
Zhe Wang
Guangyu Nie
Yassine Mazboudi
Yezhou Yang
Yi Ren
AAMLOOD
142
3
0
31 Jan 2019
Conditioning by adaptive sampling for robust design
Conditioning by adaptive sampling for robust design
David H. Brookes
Hahnbeom Park
Jennifer Listgarten
625
219
0
29 Jan 2019
SirenAttack: Generating Adversarial Audio for End-to-End Acoustic Systems
Tianyu Du
S. Ji
Jinfeng Li
Qinchen Gu
Ting Wang
Jiliang Li
AAML
249
146
0
23 Jan 2019
Universal Rules for Fooling Deep Neural Networks based Text
  Classification
Universal Rules for Fooling Deep Neural Networks based Text Classification
Di Li
Danilo Vasconcellos Vargas
Kouichi Sakurai
AAML
122
11
0
22 Jan 2019
Perception-in-the-Loop Adversarial Examples
Perception-in-the-Loop Adversarial Examples
Mahmoud Salamati
Sadegh Soudjani
R. Majumdar
AAML
81
3
0
21 Jan 2019
Generating Adversarial Perturbation with Root Mean Square Gradient
Yatie Xiao
Chi-Man Pun
Jizhe Zhou
GAN
132
1
0
13 Jan 2019
Input Prioritization for Testing Neural Networks
Input Prioritization for Testing Neural Networks
Taejoon Byun
Vaibhav Sharma
Abhishek Vijayakumar
Sanjai Rayadurgam
D. Cofer
AAML
134
73
0
11 Jan 2019
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Detecting Overfitting of Deep Generative Networks via Latent Recovery
Ryan Webster
Julien Rabin
Loïc Simon
F. Jurie
GAN
185
104
0
09 Jan 2019
Thinking Outside the Pool: Active Training Image Creation for Relative
  Attributes
Thinking Outside the Pool: Active Training Image Creation for Relative Attributes
Aron Yu
Kristen Grauman
140
23
0
08 Jan 2019
Personalized explanation in machine learning: A conceptualization
Personalized explanation in machine learning: A conceptualization
J. Schneider
J. Handali
XAIFAtt
295
18
0
03 Jan 2019
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