Vulnerable Road Users Detection and Tracking using YOLOv4 and Deep SORT

被引：0
|
作者：
Abdel-Gawad, Ahmed H. [1 ]
Khamis, Alaa [1 ,2 ]
Said, Lobna A. [1 ]
Radwan, Ahmed G. [3 ,4 ]
机构：
[1] Nile University, Nanoelectronics Integrated Systems Center, Cairo, Egypt
[2] General Motors of Canada, Canada
[3] Department of Engineering Mathematics and Physics, Cairo University, Egypt
[4] School of Engineering and Applied Sciences (EAS), Nile University, Egypt
来源：
Proceedings of the 2021 International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2021 | 2021年
关键词：
Deep SORT - Detection and tracking - Object Tracking - Objects detection - Road users - Self drivings - Self-driving vehicle - User tracking - Vulnerable road user - YOLOv4;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
26
引用
收藏
页码：140 / 145
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