IEEE Access
(Jan 2024)
Corrections to “Defending CNN Against FGSM Attacks Using Beta-Based Personalized Activation Functions and Adversarial Training”
Hanen Issaoui,
Asma Eladel,
Ahmed Zouinkhi,
Mourad Zaied,
Lazhar Khriji,
Sarvar Hussain Nengroo,
Sangkeum Lee
Affiliations
Hanen Issaoui
ORCiD Research Team in Intelligent Machines (RTIM), University of Gabes, Gabes, Tunisia
Asma Eladel
Research Team in Intelligent Machines (RTIM), University of Gabes, Gabes, Tunisia
Ahmed Zouinkhi
ORCiD MACS Laboratory LR 16ES22, National Engineering School of Gabes, University of Gabes, Gabes, Tunisia
Mourad Zaied
ORCiD Research Team in Intelligent Machines (RTIM), University of Gabes, Gabes, Tunisia
Lazhar Khriji
ORCiD Department of Electrical and Computer Engineering, College of Engineering, Sultan Qaboos University, Muscat, Oman
Sarvar Hussain Nengroo
ORCiD Department of Computer Engineering, Hanbat National University, Yuseong-gu, Daejeon, Republic of Korea
Sangkeum Lee
Cho Chun Shik Graduate School of Mobility, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
DOI
https://doi.org/10.1109/ACCESS.2024.3499512
Journal volume & issue
Vol. 12
Abstract
Read online
Presents corrections to the paper, (Corrections to “Defending CNN Against FGSM Attacks Using Beta-Based Personalized Activation Functions and Adversarial Training”).
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