A novel insulator defect detection scheme based on Deep Convolutional Auto‐Encoder for small negative samples-Reference-Cited by-同舟云学术

A novel insulator defect detection scheme based on Deep Convolutional Auto‐Encoder for small negative samples

Published:2022-04-21 Issue:5 Volume:7 Page:925-935
ISSN:2397-7264
Container-title:High Voltage
language:en
Short-container-title:High Voltage

Author:

Deng Fangming¹^ORCID,Luo Wei²,Wei Baoquan¹,Zuo Yong²,Zeng Han²^ORCID,He Yigang³

Affiliation:

1. State Key Laboratory of Performance Monitoring and Protecting of Rail Transit Infrastructure East China Jiaotong University Nanchang China

2. School of Electrical and Automation Engineering East China Jiaotong University Nanchang China

3. School of Electrical Engineering and Automation Wuhan University Wuhan China

Funder

National Natural Science Foundation of China

Key Research and Development Program of Jiangxi Province

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/hve2.12210

Reference33 articles.

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4. Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved Hough transform

5. An accurate and real‐time method of self‐blast glass insulator location based on faster R‐CNN and U‐net with aerial images;Ling Z.;CSEE J. Power Energy Syst.,2019

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