Research on mine vehicle tracking and detection technology based on YOLOv5-Reference-Cited by-同舟云学术

Research on mine vehicle tracking and detection technology based on YOLOv5

Published:2022-04-22 Issue:1 Volume:10 Page:347-366
ISSN:2164-2583
Container-title:Systems Science & Control Engineering
language:en
Short-container-title:Systems Science & Control Engineering

Author:

Zhang Kaijie¹^ORCID,Wang Chao¹²^ORCID,Yu Xiaoyong¹^ORCID,Zheng Aihua³^ORCID,Gao Mingyue¹^ORCID,Pan Zhenggao¹^ORCID,Chen Guolong⁴^ORCID,Shen Zhiqi⁵^ORCID

Affiliation:

1. School of Informatics and Engineering, Suzhou University, Suzhou, People's Republic of China

2. Institute of Machine Learning and Systems Biology, School of Electronics and Information Engineering, Tongji University, ShangHai, People's Republic of China

3. Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, HeFei, People's Republic of China

4. School of Computer Science and Information Engineering, Bengbu University, Bengbu, People's Republic of China

5. School of Computer Science and Engineering, Nanyang Technological University, Nanyang Avenue, Singapore

Funder

Suzhou University

Anhui Province

Information Materials and Intelligent Sensing Laboratory of Anhui Province

Key Scientific research projects of Suzhou University in 2021

Ministry of Education

Suzhou University Scientific Research

Key Research and Technology Development Projects of Anhui Province

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Control and Optimization,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/21642583.2022.2057370

Reference45 articles.

1. Baohua, Z., Xiaobo, L. & Junfei, Y. (2009). Vehicle segmentation method based on incremental scanning. http://www.paper.edu.cn/releasepaper/content/200910-358.

2. Interest Operator versus Gabor filtering for facial imagery classification

3. Kernel Machine-Based One-Parameter Regularized Fisher Discriminant Method for Face Recognition

4. Deep eye. (2020, August 14). Visual analysis of the wave yolov5 depth after the attack [OL], Zhihu, https://zhuanlan.zhihu.com/p/183838757

5. Desda. (2021, May 12). Yolov1 ∼ yolov5 paper interpretation and implementation details [OL], appreciation of Ramadan, https://www.cnblogs.com/sddai/p/14760055.html

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