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Vulnerability of deep neural networks for detecting COVID-19 cases from
  chest X-ray images to universal adversarial attacks

Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks

22 May 2020
Hokuto Hirano
K. Koga
Kazuhiro Takemoto
    AAML
ArXivPDFHTML

Papers citing "Vulnerability of deep neural networks for detecting COVID-19 cases from chest X-ray images to universal adversarial attacks"

4 / 4 papers shown
Title
On Evaluating Adversarial Robustness of Chest X-ray Classification:
  Pitfalls and Best Practices
On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices
Salah Ghamizi
Maxime Cordy
Michail Papadakis
Yves Le Traon
OOD
11
2
0
15 Dec 2022
Automated Detection and Forecasting of COVID-19 using Deep Learning
  Techniques: A Review
Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review
A. Shoeibi
Marjane Khodatars
M. Jafari
Navid Ghassemi
Delaram Sadeghi
...
Z. Sani
F. Khozeimeh
S. Nahavandi
U. Acharya
Juan M Gorriz
51
178
0
16 Jul 2020
A New Defense Against Adversarial Images: Turning a Weakness into a
  Strength
A New Defense Against Adversarial Images: Turning a Weakness into a Strength
Tao Yu
Shengyuan Hu
Chuan Guo
Wei-Lun Chao
Kilian Q. Weinberger
AAML
58
101
0
16 Oct 2019
A Survey on Deep Learning in Medical Image Analysis
A Survey on Deep Learning in Medical Image Analysis
G. Litjens
Thijs Kooi
B. Bejnordi
A. Setio
F. Ciompi
Mohsen Ghafoorian
Jeroen van der Laak
Bram van Ginneken
C. I. Sánchez
OOD
337
10,633
0
19 Feb 2017
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