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A Geometrical Approach to Evaluate the Adversarial Robustness of Deep
  Neural Networks

A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks

10 October 2023
Yang Wang
B. Dong
Ke Xu
Haiyin Piao
Yufei Ding
Baocai Yin
Xin Yang
    AAML
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Papers citing "A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks"

3 / 3 papers shown
Title
Object Tracking by Jointly Exploiting Frame and Event Domain
Object Tracking by Jointly Exploiting Frame and Event Domain
Jiqing Zhang
Xin Yang
Yingkai Fu
Xiaopeng Wei
Baocai Yin
B. Dong
69
84
0
19 Sep 2021
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks
Guy Katz
Clark W. Barrett
D. Dill
Kyle D. Julian
Mykel Kochenderfer
AAML
222
1,832
0
03 Feb 2017
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,830
0
08 Jul 2016
1