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On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices
Ghamizi, Salah; Cordy, Maxime; Papadakis, Mike et al.
2022In The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI- 23) - SafeAI Workshop, Washington, D.C., Feb 13-14, 2023
Peer reviewed
 

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Keywords :
Chest X-ray; Adversarial Robustness; Evasion attacks; CXR; Radiograph; NIH; PadChest; CheXpert
Disciplines :
Computer science
Author, co-author :
Ghamizi, Salah ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Cordy, Maxime  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Papadakis, Mike ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Le Traon, Yves ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
External co-authors :
no
Language :
English
Title :
On Evaluating Adversarial Robustness of Chest X-ray Classification: Pitfalls and Best Practices
Publication date :
2022
Event name :
The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI- 23) - SafeAI
Event date :
07-02-2023 14-02-2023
Audience :
International
Main work title :
The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI- 23) - SafeAI Workshop, Washington, D.C., Feb 13-14, 2023
Peer reviewed :
Peer reviewed
Focus Area :
Security, Reliability and Trust
Available on ORBilu :
since 12 January 2023

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