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Characterizing and evaluating adversarial examples for Offline
  Handwritten Signature Verification

Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification

10 January 2019
L. G. Hafemann
R. Sabourin
Luiz Eduardo Soares de Oliveira
    AAML
ArXivPDFHTML

Papers citing "Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification"

5 / 5 papers shown
Title
Deep representation learning: Fundamentals, Perspectives, Applications,
  and Open Challenges
Deep representation learning: Fundamentals, Perspectives, Applications, and Open Challenges
K. T. Baghaei
Amirreza Payandeh
Pooya Fayyazsanavi
Shahram Rahimi
Zhiqian Chen
Somayeh Bakhtiari Ramezani
FaML
AI4TS
38
6
0
27 Nov 2022
A Survey of PPG's Application in Authentication
A Survey of PPG's Application in Authentication
Lin Li
Chao Chen
Lei Pan
Leo Yu Zhang
Zhifeng Wang
Jun Zhang
Yang Xiang
31
13
0
27 Jan 2022
Demystifying the Transferability of Adversarial Attacks in Computer
  Networks
Demystifying the Transferability of Adversarial Attacks in Computer Networks
Ehsan Nowroozi
Yassine Mekdad
Mohammad Hajian Berenjestanaki
Mauro Conti
Abdeslam El Fergougui
AAML
42
32
0
09 Oct 2021
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
296
3,113
0
04 Nov 2016
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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