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Improved edge lightweight YOLOv4 and its application in on-site power system work

Kexin Li Liang Qin Qiang Li Feng Zhao Zhongping Xu Kaipei Liu

全球能源互联网：英文版2022，Vol.5Issue(2)：P.168-180,13.

全球能源互联网：英文版2022，Vol.5Issue(2)：P.168-180,13.DOI:10.1016/j.gloei.2022.04.014

Improved edge lightweight YOLOv4 and its application in on-site power system work

Kexin Li ¹Liang Qin ¹Qiang Li ²Feng Zhao ²Zhongping Xu ³Kaipei Liu¹

作者信息

1. School of Electrical Engineering and Automation,Wuhan Universtiy,Wuhan,430072,P.R.China
2. State Grid Information&Telecommunication Group Co.,Ltd,Beijing,102211,P.R.China
3. Beijing State Grid Information&Telecommunication Accenture Information Technology Co.,Ltd.Beijing 100052,P.R.China
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摘要

关键词

On-site power system work/YOLOv4-Tiny/Convolution block attention mechanism/Efficient channel attention/Optimized training methods.

分类

信息技术与安全科学

引用本文复制引用

Kexin Li,Liang Qin,Qiang Li,Feng Zhao,Zhongping Xu,Kaipei Liu..Improved edge lightweight YOLOv4 and its application in on-site power system work[J].全球能源互联网：英文版,2022,5(2):P.168-180,13.

基金项目

supported by the Science and technology project of State Grid Information&Telecommunication Group Co.,Ltd (SGTYHT/19-JS-218) （SGTYHT/19-JS-218）

全球能源互联网：英文版

OACSCDCSTPCDEI

ISSN：2096-5117

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