TTH LE, et al., 'Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images with Different Patch Sizes and Perturbation Ratios', IEEE Access 9, 2021


제목	TTH LE, et al., "Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images with Different Patch Sizes and Perturbation Ratios", IEEE Access 9, 20212022-01-04 15:31
카테고리	SCI paper
작성자	infosec

이전	Jinjae Lee, et al., "CoMeT: Configurable Tagged Memory Extension", sensors, 21(22), 202111	infosec	2022-01-04
-	TTH LE, et al., "Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images with Different Patch Sizes and Perturbation Ratios", IEEE Access 9, 2021	infosec	2022-01-04
다음	Ludia Eka Feri, et al., "A Three-Dimensional Microstructure Reconstruction Framework for Permeable Pavement Analysis Based on 3D-IWGAN with Enhanced Gradient Penalty", Sensors 21(11), 202105	infosec	2021-08-11