Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Linchengxi Zeng"'
Publikováno v:
IEEE Access, Vol 11, Pp 89369-89382 (2023)
Deep face recognition models are vulnerable to adversarial samples generated by adversarial attack methods. However, current attack methods do not adequately represent the security problems of the deep FR models, because they either produce adversari
Externí odkaz:
https://doaj.org/article/b6a91c783f404e658c1c799bf06a26cb
Publikováno v:
2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application (HPCC/DSS/SmartCity/DependSys).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5d42375b671d428eb7e1540360288781
https://doi.org/10.1109/hpcc-dss-smartcity-dependsys57074.2022.00061
https://doi.org/10.1109/hpcc-dss-smartcity-dependsys57074.2022.00061
Autor:
Hui Zhu, Yongchun Lu, Hongbin Wang, Xunyi Zhou, Qin Ma, Yanhong Liu, Ning Jiang, Xin Wei, Linchengxi Zeng, Xiaofang Zhao
Publikováno v:
Proceedings of the 30th ACM International Conference on Multimedia.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e5e3821af848944537ad4cc41a8f0341
https://doi.org/10.1145/3503161.3548026
https://doi.org/10.1145/3503161.3548026
Autor:
Yifei Lv, Kunyin Guo, Yunni Xia, Yin Li, Yong Ma, Fan Li, Linchengxi Zeng, Qinglan Peng, Tingyan Long
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031235788
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3c8b3661bbe426c2bffe55075f7025c5
https://doi.org/10.1007/978-3-031-23579-5_4
https://doi.org/10.1007/978-3-031-23579-5_4
