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An Accurate and Real-time Method of Self-blast Glass Insulator Location Based on Faster R-CNN and U-net with Aerial Images

Zenan Ling Dongxia Zhang Robert C.Qiu Zhijian Jin Yuhang Zhang Xing He Haichun Liu

中国电机工程学会电力与能源系统学报（英文版）2019，Vol.5Issue(4)：474-482,9.

中国电机工程学会电力与能源系统学报（英文版）2019，Vol.5Issue(4)：474-482,9.DOI:10.17775/CSEEJPES.2019.00460

An Accurate and Real-time Method of Self-blast Glass Insulator Location Based on Faster R-CNN and U-net with Aerial Images

Zenan Ling ¹Dongxia Zhang ²Robert C.Qiu ³Zhijian Jin ¹Yuhang Zhang ¹Xing He ¹Haichun Liu¹

作者信息

1. Department of Electrical Engineering,Center for Big Data and Artificial Intelligence,State Energy Smart Grid Research and Development Center,Shanghai Jiao Tong University,Shanghai 200240,China
2. China Electric Power Research Institute,Beijing 100192,China
3. Department of Electrical and Computer Engineering,Tennessee Technological University,Cookeville,TN 38505,USA
折叠

摘要

关键词

Aerial images/deep learning/faster R-CNN/insulators/location/real-time/U-net

Key words

Aerial images/deep learning/faster R-CNN/insulators/location/real-time/U-net

引用本文复制引用

Zenan Ling,Dongxia Zhang,Robert C.Qiu,Zhijian Jin,Yuhang Zhang,Xing He,Haichun Liu..An Accurate and Real-time Method of Self-blast Glass Insulator Location Based on Faster R-CNN and U-net with Aerial Images[J].中国电机工程学会电力与能源系统学报（英文版）,2019,5(4):474-482,9.

基金项目

This work was supported in part by the National Natural Science Foundation of China (No. 61571296) and the National Science Foundation of USA (No. CNS-1619250). （No. 61571296）

中国电机工程学会电力与能源系统学报（英文版）

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ISSN：2096-0042

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