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Adversarial Examples Detection in Deep Networks with Convolutional
  Filter Statistics

Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics

22 December 2016
Xin Li
Fuxin Li
    GAN
    AAML
ArXivPDFHTML

Papers citing "Adversarial Examples Detection in Deep Networks with Convolutional Filter Statistics"

15 / 65 papers shown
Title
A Comprehensive Overview of Biometric Fusion
A Comprehensive Overview of Biometric Fusion
Maneet Singh
Richa Singh
Arun Ross
16
185
0
08 Feb 2019
Controlling Over-generalization and its Effect on Adversarial Examples
  Generation and Detection
Controlling Over-generalization and its Effect on Adversarial Examples Generation and Detection
Mahdieh Abbasi
Arezoo Rajabi
A. Mozafari
R. Bobba
Christian Gagné
AAML
24
9
0
21 Aug 2018
Motivating the Rules of the Game for Adversarial Example Research
Motivating the Rules of the Game for Adversarial Example Research
Justin Gilmer
Ryan P. Adams
Ian Goodfellow
David G. Andersen
George E. Dahl
AAML
50
226
0
18 Jul 2018
Detection based Defense against Adversarial Examples from the
  Steganalysis Point of View
Detection based Defense against Adversarial Examples from the Steganalysis Point of View
Jiayang Liu
Weiming Zhang
Yiwei Zhang
Dongdong Hou
Yujia Liu
Hongyue Zha
Nenghai Yu
AAML
25
98
0
21 Jun 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with
  Out-distribution Learning
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning
Mahdieh Abbasi
Arezoo Rajabi
Christian Gagné
R. Bobba
OODD
30
6
0
24 Apr 2018
Characterizing Adversarial Subspaces Using Local Intrinsic
  Dimensionality
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma
Bo-wen Li
Yisen Wang
S. Erfani
S. Wijewickrema
Grant Schoenebeck
D. Song
Michael E. Houle
James Bailey
AAML
43
728
0
08 Jan 2018
ReabsNet: Detecting and Revising Adversarial Examples
ReabsNet: Detecting and Revising Adversarial Examples
Jiefeng Chen
Zihang Meng
Changtian Sun
Weiliang Tang
Yinglun Zhu
AAML
GAN
26
4
0
21 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning
Battista Biggio
Fabio Roli
AAML
40
1,390
0
08 Dec 2017
Detecting Adversarial Attacks on Neural Network Policies with Visual
  Foresight
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight
Yen-Chen Lin
Ming Liu
Min Sun
Jia-Bin Huang
AAML
29
48
0
02 Oct 2017
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the
  iCub Humanoid
Is Deep Learning Safe for Robot Vision? Adversarial Examples against the iCub Humanoid
Marco Melis
Ambra Demontis
Battista Biggio
Gavin Brown
Giorgio Fumera
Fabio Roli
AAML
21
98
0
23 Aug 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive
  Noise Reduction
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction
Bin Liang
Hongcheng Li
Miaoqiang Su
Xirong Li
Wenchang Shi
Xiaofeng Wang
AAML
12
215
0
23 May 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection
  Methods
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods
Nicholas Carlini
D. Wagner
AAML
61
1,842
0
20 May 2017
DeepCorrect: Correcting DNN models against Image Distortions
DeepCorrect: Correcting DNN models against Image Distortions
Tejas S. Borkar
Lina Karam
27
93
0
05 May 2017
On the (Statistical) Detection of Adversarial Examples
On the (Statistical) Detection of Adversarial Examples
Kathrin Grosse
Praveen Manoharan
Nicolas Papernot
Michael Backes
Patrick McDaniel
AAML
39
709
0
21 Feb 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
317
5,847
0
08 Jul 2016
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