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Polarizing Front Ends for Robust CNNs

Polarizing Front Ends for Robust CNNs

IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
22 February 2020
Can Bakiskan
S. Gopalakrishnan
Metehan Cekic
Upamanyu Madhow
Ramtin Pedarsani
    AAML
ArXiv (abs)PDFHTML

Papers citing "Polarizing Front Ends for Robust CNNs"

3 / 3 papers shown
Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis
  Testing
Generalized Likelihood Ratio Test for Adversarially Robust Hypothesis TestingIEEE Transactions on Signal Processing (IEEE TSP), 2021
Bhagyashree Puranik
Upamanyu Madhow
Ramtin Pedarsani
AAML
149
7
0
04 Dec 2021
A Neuro-Inspired Autoencoding Defense Against Adversarial Perturbations
A Neuro-Inspired Autoencoding Defense Against Adversarial Perturbations
Can Bakiskan
Metehan Cekic
Ahmet Dundar Sezer
Upamanyu Madhow
AAML
176
1
0
21 Nov 2020
Adversarially Robust Classification based on GLRT
Adversarially Robust Classification based on GLRTIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020
Bhagyashree Puranik
Upamanyu Madhow
Ramtin Pedarsani
VLMAAML
220
4
0
16 Nov 2020
1
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