THI-THU-HUONG LE, et al, 'Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images with Different Patch Sizes and Perturbation Ratios', IEEE Acces

주요 연구결과물[관리자]

HOME > 구성원 > 주요 연구결과물[관리자]

주요 연구결과물[관리자]

Home / 주요 연구결과물[관리자]


제목	THI-THU-HUONG LE, et al, "Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images with Different Patch Sizes and Perturbation Ratios", IEEE Acces2022-01-04 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
다음	Ludia Eka Feri, at 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

betgaranti giriş bets10 onwin giriş PUSULABET holiganbet guncel giris