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2209.04779
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Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense
11 September 2022
Bo Peng
Bo Peng
Jie Zhou
Jianyue Xie
Li Liu
AAML
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Papers citing
"Scattering Model Guided Adversarial Examples for SAR Target Recognition: Attack and Defense"
37 / 37 papers shown
Title
Universal Adversarial Examples in Remote Sensing: Methodology and Benchmark
Yonghao Xu
Pedram Ghamisi
AAML
56
72
0
14 Feb 2022
Attentional Feature Refinement and Alignment Network for Aircraft Detection in SAR Imagery
Yan Zhao
Lingjun Zhao
Zhongkang Liu
Dewen Hu
Gangyao Kuang
Li Liu
54
32
0
18 Jan 2022
Universal Spectral Adversarial Attacks for Deformable Shapes
Arianna Rampini
Franco Pestarini
Luca Cosmo
Simone Melzi
Emanuele Rodolà
AAML
101
18
0
07 Apr 2021
Adversarial Laser Beam: Effective Physical-World Attack to DNNs in a Blink
Ranjie Duan
Xiaofeng Mao
•. A. K. Qin
Yun Yang
YueFeng Chen
Shaokai Ye
Yuan He
AAML
43
139
0
11 Mar 2021
Invisible Perturbations: Physical Adversarial Examples Exploiting the Rolling Shutter Effect
Athena Sayles
Ashish Hooda
M. Gupta
Rahul Chatterjee
Earlence Fernandes
AAML
51
77
0
26 Nov 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness
Guillermo Ortiz-Jiménez
Apostolos Modas
Seyed-Mohsen Moosavi-Dezfooli
P. Frossard
AAML
93
48
0
19 Oct 2020
Automatic Target Recognition on Synthetic Aperture Radar Imagery: A Survey
O. Kechagias-Stamatis
N. Aouf
26
106
0
04 Jul 2020
Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce
Maksym Andriushchenko
Naman D. Singh
Nicolas Flammarion
Matthias Hein
83
101
0
23 Jun 2020
Deep Learning Meets SAR
Xiaoxiang Zhu
S. Montazeri
Mohsin Ali
Yuansheng Hua
Yuanyuan Wang
Lichao Mou
Yilei Shi
Feng Xu
R. Bamler
74
223
0
17 Jun 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
520
42,559
0
03 Dec 2019
Sparse and Imperceivable Adversarial Attacks
Francesco Croce
Matthias Hein
AAML
97
199
0
11 Sep 2019
Functional Adversarial Attacks
Cassidy Laidlaw
Soheil Feizi
AAML
72
185
0
29 May 2019
Adversarial Examples Are Not Bugs, They Are Features
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
SILM
91
1,843
0
06 May 2019
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
Eric Wong
Frank R. Schmidt
J. Zico Kolter
AAML
78
211
0
21 Feb 2019
Deep Learning for Generic Object Detection: A Survey
Li Liu
Wanli Ouyang
Xiaogang Wang
Paul Fieguth
Jie Chen
Xinwang Liu
M. Pietikäinen
ObjD
VLM
OOD
162
2,456
0
06 Sep 2018
ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design
Ningning Ma
Xiangyu Zhang
Haitao Zheng
Jian Sun
181
5,000
0
30 Jul 2018
Invisible Mask: Practical Attacks on Face Recognition with Infrared
Zhe Zhou
Di Tang
Xiaofeng Wang
Weili Han
Xiangyu Liu
Kehuan Zhang
CVBM
AAML
66
103
0
13 Mar 2018
Texture Classification in Extreme Scale Variations using GANet
Li Liu
Jie Chen
Guoying Zhao
Paul Fieguth
Xilin Chen
M. Pietikäinen
24
22
0
13 Feb 2018
MobileNetV2: Inverted Residuals and Linear Bottlenecks
Mark Sandler
Andrew G. Howard
Menglong Zhu
A. Zhmoginov
Liang-Chieh Chen
186
19,316
0
13 Jan 2018
LaVAN: Localized and Visible Adversarial Noise
D. Karmon
Daniel Zoran
Yoav Goldberg
AAML
75
244
0
08 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Naveed Akhtar
Ajmal Mian
AAML
97
1,871
0
02 Jan 2018
Countering Adversarial Images using Input Transformations
Chuan Guo
Mayank Rana
Moustapha Cissé
Laurens van der Maaten
AAML
120
1,406
0
31 Oct 2017
Towards Deep Learning Models Resistant to Adversarial Attacks
Aleksander Madry
Aleksandar Makelov
Ludwig Schmidt
Dimitris Tsipras
Adrian Vladu
SILM
OOD
310
12,117
0
19 Jun 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
Weilin Xu
David Evans
Yanjun Qi
AAML
87
1,271
0
04 Apr 2017
A Boundary Tilting Persepective on the Phenomenon of Adversarial Examples
T. Tanay
Lewis D. Griffin
AAML
85
272
0
27 Aug 2016
Densely Connected Convolutional Networks
Gao Huang
Zhuang Liu
Laurens van der Maaten
Kilian Q. Weinberger
PINN
3DV
775
36,861
0
25 Aug 2016
Towards Evaluating the Robustness of Neural Networks
Nicholas Carlini
D. Wagner
OOD
AAML
266
8,579
0
16 Aug 2016
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
545
5,909
0
08 Jul 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size
F. Iandola
Song Han
Matthew W. Moskewicz
Khalid Ashraf
W. Dally
Kurt Keutzer
153
7,495
0
24 Feb 2016
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,322
0
10 Dec 2015
The Limitations of Deep Learning in Adversarial Settings
Nicolas Papernot
Patrick McDaniel
S. Jha
Matt Fredrikson
Z. Berkay Celik
A. Swami
AAML
112
3,966
0
24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks
Seyed-Mohsen Moosavi-Dezfooli
Alhussein Fawzi
P. Frossard
AAML
151
4,903
0
14 Nov 2015
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
248
4,681
0
21 Dec 2014
Explaining and Harnessing Adversarial Examples
Ian Goodfellow
Jonathon Shlens
Christian Szegedy
AAML
GAN
280
19,107
0
20 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Totti Nguyen
J. Yosinski
Jeff Clune
AAML
171
3,275
0
05 Dec 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAtt
MDE
1.7K
100,479
0
04 Sep 2014
Intriguing properties of neural networks
Christian Szegedy
Wojciech Zaremba
Ilya Sutskever
Joan Bruna
D. Erhan
Ian Goodfellow
Rob Fergus
AAML
277
14,961
1
21 Dec 2013
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