Deep learning technology for re-identification of people and vehicles

被引:4
作者
Wang, Yixiong [1 ]
机构
[1] Auburn Univ, Sch Auburn, Auburn, AL 36849 USA
来源
2022 IEEE INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING, BIG DATA AND ALGORITHMS (EEBDA) | 2022年
关键词
recognitions; re-identifications; algorithm; image; vehicles; plates;
D O I
10.1109/EEBDA53927.2022.9744971
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article contains and explains the deep learning, especially different kinds of re-identifications. Deep learning which is contained in this article including vehicle reidentification, pedestrian re-identification and facial completion. This article defines these three kinds of reidentifications, and also explains and compares the methods which uses to actually do re-identifications. It also introduces some algorithms, it talks about how the algorithms come out, how to use it, and what problems do different algorithms have, what kind of future goals can be made, and what needs to be developed. Although the field of recognitions has already achieved some goals recently, there are still many challenges need to be solved.
引用
收藏
页码:972 / 975
页数:4
相关论文
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Liang Xinyu, 2020, ACTA ELECT SINICA, V48No
[2]  
Liu Ying, 2020, REV FACIAL REPAIR TE, P04
[3]  
Wei Wenyu, 2020, 19 KOLI CALLING C CO, P06
[4]  
Xu Tao, 2020, ACM SIGGRAPH 2020 EM, P10
[5]  
Zhang Xiaorui, 2020, RES PROGR VEHICLE RE