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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
Robust Deep Learning Ensemble against Deception
Robust Deep Learning Ensemble against DeceptionIEEE Transactions on Dependable and Secure Computing (TDSC), 2020
Wenqi Wei
Ling Liu
AAML
144
29
0
14 Sep 2020
Why I'm not Answering: Understanding Determinants of Classification of
  an Abstaining Classifier for Cancer Pathology Reports
Why I'm not Answering: Understanding Determinants of Classification of an Abstaining Classifier for Cancer Pathology Reports
S. Dhaubhadel
J. Mohd-Yusof
K. Ganguly
Gopinath Chennupati
S. Thulasidasan
...
Georgia D. Tourassi
Linda Coyle
Lynne Penberthy
Benjamin H. McMahon
T. Bhattacharya
258
2
0
10 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards
  the Defender's Perspective
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's PerspectiveACM Computing Surveys (ACM CSUR), 2020
G. R. Machado
Eugênio Silva
R. Goldschmidt
AAML
256
182
0
08 Sep 2020
Transparency and granularity in the SP Theory of Intelligence and its
  realisation in the SP Computer Model
Transparency and granularity in the SP Theory of Intelligence and its realisation in the SP Computer ModelStudies in Computational Intelligence (SCI), 2020
J. Wolff
199
5
0
07 Sep 2020
Problems in AI research and how the SP System may help to solve them
Problems in AI research and how the SP System may help to solve them
J. G. Wolff
215
2
0
02 Sep 2020
Adversarially Robust Neural Architectures
Adversarially Robust Neural ArchitecturesIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020
Minjing Dong
Yanxi Li
Yunhe Wang
Chang Xu
AAMLOOD
275
51
0
02 Sep 2020
Inducing Predictive Uncertainty Estimation for Face Recognition
Inducing Predictive Uncertainty Estimation for Face RecognitionBritish Machine Vision Conference (BMVC), 2020
Weidi Xie
J. Byrne
Andrew Zisserman
CVBM
159
19
0
01 Sep 2020
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
SDE-Net: Equipping Deep Neural Networks with Uncertainty Estimates
Lingkai Kong
Jimeng Sun
Chao Zhang
UQCV
212
127
0
24 Aug 2020
Perceptual underwater image enhancement with deep learning and physical
  priors
Perceptual underwater image enhancement with deep learning and physical priors
Long Chen
Zheheng Jiang
Lei Tong
Zhihua Liu
Aite Zhao
Qianni Zhang
Junyu Dong
Huiyu Zhou
147
32
0
21 Aug 2020
A Survey on Assessing the Generalization Envelope of Deep Neural
  Networks: Predictive Uncertainty, Out-of-distribution and Adversarial Samples
A Survey on Assessing the Generalization Envelope of Deep Neural Networks: Predictive Uncertainty, Out-of-distribution and Adversarial Samples
Julia Lust
Alexandru Paul Condurache
UQCVAAMLAI4CE
218
8
0
21 Aug 2020
Feature Extraction Functions for Neural Logic Rule Learning
Feature Extraction Functions for Neural Logic Rule Learning
Shashank Gupta
A. Robles-Kelly
Mohamed Reda Bouadjenek
NAI
114
0
0
14 Aug 2020
Optimizing Information Loss Towards Robust Neural Networks
Optimizing Information Loss Towards Robust Neural Networks
Philip Sperl
Konstantin Böttinger
AAML
160
3
0
07 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey
Adversarial Examples on Object Recognition: A Comprehensive SurveyACM Computing Surveys (ACM CSUR), 2020
A. Serban
E. Poll
Joost Visser
AAML
417
80
0
07 Aug 2020
Vulnerability Under Adversarial Machine Learning: Bias or Variance?
Vulnerability Under Adversarial Machine Learning: Bias or Variance?
Hossein Aboutalebi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
AAML
157
3
0
01 Aug 2020
A General Framework For Detecting Anomalous Inputs to DNN Classifiers
A General Framework For Detecting Anomalous Inputs to DNN ClassifiersInternational Conference on Machine Learning (ICML), 2020
Jayaram Raghuram
Varun Chandrasekaran
S. Jha
Suman Banerjee
AAML
253
38
0
29 Jul 2020
AI Data poisoning attack: Manipulating game AI of Go
AI Data poisoning attack: Manipulating game AI of Go
Junli Shen
Maocai Xia
AAML
156
3
0
23 Jul 2020
Inverting the Feature Visualization Process for Feedforward Neural
  Networks
Inverting the Feature Visualization Process for Feedforward Neural Networks
Christian Reinbold
Rüdiger Westermann
FAtt
128
0
0
21 Jul 2020
AdvFoolGen: Creating Persistent Troubles for Deep Classifiers
AdvFoolGen: Creating Persistent Troubles for Deep Classifiers
Yuzhen Ding
Nupur Thakur
Baoxin Li
AAML
158
3
0
20 Jul 2020
DiffRNN: Differential Verification of Recurrent Neural Networks
DiffRNN: Differential Verification of Recurrent Neural Networks
Sara Mohammadinejad
Brandon Paulsen
Chao Wang
Jyotirmoy V. Deshmukh
213
13
0
20 Jul 2020
Evaluating a Simple Retraining Strategy as a Defense Against Adversarial
  Attacks
Evaluating a Simple Retraining Strategy as a Defense Against Adversarial Attacks
Nupur Thakur
Yuzhen Ding
Baoxin Li
AAML
62
3
0
20 Jul 2020
Technologies for Trustworthy Machine Learning: A Survey in a
  Socio-Technical Context
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
Ehsan Toreini
Mhairi Aitken
Kovila P. L. Coopamootoo
Karen Elliott
Vladimiro González-Zelaya
P. Missier
Magdalene Ng
Aad van Moorsel
307
19
0
17 Jul 2020
Camera Bias in a Fine Grained Classification Task
Camera Bias in a Fine Grained Classification TaskIEEE International Joint Conference on Neural Network (IJCNN), 2020
Philip T. G. Jackson
Stephen Bonner
Ning Jia
Christopher J. Holder
Jonathan Stonehouse
B. Obara
131
4
0
16 Jul 2020
Certifiably Adversarially Robust Detection of Out-of-Distribution Data
Certifiably Adversarially Robust Detection of Out-of-Distribution Data
Julian Bitterwolf
Alexander Meinke
Matthias Hein
341
9
0
16 Jul 2020
Nested Learning For Multi-Granular Tasks
Nested Learning For Multi-Granular Tasks
Raphaël Achddou
J. Matias Di Martino
Guillermo Sapiro
141
1
0
13 Jul 2020
Seeing eye-to-eye? A comparison of object recognition performance in
  humans and deep convolutional neural networks under image manipulation
Seeing eye-to-eye? A comparison of object recognition performance in humans and deep convolutional neural networks under image manipulation
Leonard E. van Dyck
W. Gruber
209
4
0
13 Jul 2020
Contrastive Training for Improved Out-of-Distribution Detection
Contrastive Training for Improved Out-of-Distribution Detection
Jim Winkens
Rudy Bunel
Abhijit Guha Roy
Robert Stanforth
Vivek Natarajan
...
Alan Karthikesalingam
Simon A. A. Kohl
taylan. cemgil
S. M. Ali Eslami
Olaf Ronneberger
OODD
369
258
0
10 Jul 2020
Boundary thickness and robustness in learning models
Boundary thickness and robustness in learning modelsNeural Information Processing Systems (NeurIPS), 2020
Yaoqing Yang
Rekha Khanna
Yaodong Yu
A. Gholami
Kurt Keutzer
Joseph E. Gonzalez
Kannan Ramchandran
Michael W. Mahoney
OOD
218
46
0
09 Jul 2020
Detection of Gravitational Waves Using Bayesian Neural Networks
Detection of Gravitational Waves Using Bayesian Neural Networks
Yu-Chiung Lin
Jiun-Huei Proty Wu
228
29
0
08 Jul 2020
MCU-Net: A framework towards uncertainty representations for decision
  support system patient referrals in healthcare contexts
MCU-Net: A framework towards uncertainty representations for decision support system patient referrals in healthcare contexts
Nabeel Seedat
OOD
203
7
0
08 Jul 2020
Soft Labeling Affects Out-of-Distribution Detection of Deep Neural
  Networks
Soft Labeling Affects Out-of-Distribution Detection of Deep Neural Networks
Doyup Lee
Yeongjae Cheon
93
6
0
07 Jul 2020
Confidence-Aware Learning for Deep Neural Networks
Confidence-Aware Learning for Deep Neural Networks
J. Moon
Jihyo Kim
Younghak Shin
Sangheum Hwang
UQCV
390
170
0
03 Jul 2020
Outlier Detection through Null Space Analysis of Neural Networks
Outlier Detection through Null Space Analysis of Neural Networks
Matthew Cook
A. Zare
P. Gader
113
24
0
02 Jul 2020
Are there any óbject detectors' in the hidden layers of CNNs trained to
  identify objects or scenes?
Are there any óbject detectors' in the hidden layers of CNNs trained to identify objects or scenes?
E. Gale
Nicholas Martin
R. Blything
Anh Nguyen
J. Bowers
138
15
0
02 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A
  Survey
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey
S. Silva
Peyman Najafirad
AAMLOOD
319
148
0
01 Jul 2020
Drug discovery with explainable artificial intelligence
Drug discovery with explainable artificial intelligence
José Jiménez-Luna
F. Grisoni
G. Schneider
372
732
0
01 Jul 2020
Generating Adversarial Examples with an Optimized Quality
Generating Adversarial Examples with an Optimized Quality
Aminollah Khormali
Daehun Nyang
David A. Mohaisen
AAML
119
2
0
30 Jun 2020
Classification Confidence Estimation with Test-Time Data-Augmentation
Classification Confidence Estimation with Test-Time Data-Augmentation
Yuval Bahat
Gregory Shakhnarovich
116
20
0
30 Jun 2020
The Effect of Optimization Methods on the Robustness of
  Out-of-Distribution Detection Approaches
The Effect of Optimization Methods on the Robustness of Out-of-Distribution Detection Approaches
Vahdat Abdelzad
Krzysztof Czarnecki
Rick Salay
161
1
0
25 Jun 2020
Anomaly Detection in Medical Imaging with Deep Perceptual Autoencoders
Anomaly Detection in Medical Imaging with Deep Perceptual AutoencodersIEEE Access (IEEE Access), 2020
Nina Shvetsova
Bart Bakker
Irina Fedulova
H. Schulz
Dmitry V. Dylov
262
114
0
23 Jun 2020
Self-Knowledge Distillation with Progressive Refinement of Targets
Self-Knowledge Distillation with Progressive Refinement of Targets
Kyungyul Kim
Byeongmoon Ji
Doyoung Yoon
Sangheum Hwang
ODL
422
234
0
22 Jun 2020
Towards an Adversarially Robust Normalization Approach
Towards an Adversarially Robust Normalization Approach
Muhammad Awais
Fahad Shamshad
Sung-Ho Bae
AAMLOOD
219
21
0
19 Jun 2020
Adversarial Attacks for Multi-view Deep Models
Adversarial Attacks for Multi-view Deep Models
Xuli Sun
Shiliang Sun
AAML
102
0
0
19 Jun 2020
Fourier Features Let Networks Learn High Frequency Functions in Low
  Dimensional Domains
Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains
Matthew Tancik
Pratul P. Srinivasan
B. Mildenhall
Sara Fridovich-Keil
N. Raghavan
Utkarsh Singhal
R. Ramamoorthi
Jonathan T. Barron
Ren Ng
577
3,037
0
18 Jun 2020
The shape and simplicity biases of adversarially robust ImageNet-trained
  CNNs
The shape and simplicity biases of adversarially robust ImageNet-trained CNNs
Peijie Chen
Chirag Agarwal
Anh Totti Nguyen
AAML
400
18
0
16 Jun 2020
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and
  Faster Adversarial Robustness Proofs
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness Proofs
Christopher Brix
T. Noll
AAML
146
11
0
16 Jun 2020
SPLASH: Learnable Activation Functions for Improving Accuracy and
  Adversarial Robustness
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness
Mohammadamin Tavakoli
Forest Agostinelli
Pierre Baldi
AAMLFAtt
290
43
0
16 Jun 2020
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data
Zhun Deng
Linjun Zhang
Amirata Ghorbani
James Zou
197
32
0
15 Jun 2020
Depth Uncertainty in Neural Networks
Depth Uncertainty in Neural Networks
Javier Antorán
J. Allingham
José Miguel Hernández-Lobato
UQCVOODBDL
406
113
0
15 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks
The Pitfalls of Simplicity Bias in Neural NetworksNeural Information Processing Systems (NeurIPS), 2020
Harshay Shah
Kaustav Tamuly
Aditi Raghunathan
Prateek Jain
Praneeth Netrapalli
AAML
332
419
0
13 Jun 2020
Towards Robust Pattern Recognition: A Review
Towards Robust Pattern Recognition: A ReviewProceedings of the IEEE (Proc. IEEE), 2020
Xu-Yao Zhang
Cheng-Lin Liu
C. Suen
OODHAI
204
126
0
12 Jun 2020
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