Insulator Detection Method Based on Improved Faster R-CNN with Aerial Images-Reference-Cited by-同舟云学术

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Insulator Detection Method Based on Improved Faster R-CNN with Aerial Images

Published:2021-08 Issue: Volume: Page:
ISSN:
Container-title:2021 2nd International Symposium on Computer Engineering and Intelligent Communications (ISCEIC)
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Author:

Lu Weikuan,Zhou Zhili,Ruan Xiukai,Yan Zhengbing,Cui Guihua

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9599147/9599093/09599213.pdf?arnumber=9599213

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing the reliability of power grids: A YOLO based approach for insulator defect detection;e-Prime - Advances in Electrical Engineering, Electronics and Energy;2024-09

2. Research on an Improved Detection Algorithm Based on YOLOv5s for Power Line Self-Exploding Insulators;Electronics;2023-08-31

3. Insu-YOLO: An Insulator Defect Detection Algorithm Based on Multiscale Feature Fusion;Electronics;2023-07-25

4. The Machine Learning Model with Hybrid Pooling Approach For Transmission Line Insulator Classification and Faults Detection;2023 3rd International Conference on Intelligent Technologies (CONIT);2023-06-23

5. Automated Surface Defect Detection for Hot-Pressed Light Guide Plates Based on GDA-YOLOv7;IEEE Access;2023

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