Lightweight network for insulator fault detection based on improved YOLOv5
Author:
Affiliation:
1. College of Electrical and Electronic Engineering, Wenzhou University, Wenzhou, People's Republic of China
2. Yalong Intelligent Equipment Group, Wenzhou, People's Republic of China
Funder
scientific research project of Wenzhou
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/09540091.2023.2284090
Reference31 articles.
1. A deep learning approach for insulator instance segmentation and defect detection
2. Chollet F.. (2017). Xception: Deep learning with depthwise separable convolutions.
3. Uncertainty-aware accurate insulator fault detection based on an improved YOLOX model
4. Research on edge intelligent recognition method oriented to transmission line insulator fault detection
5. Gabor-YOLONet: A lightweight and efficient detection network for low-voltage power lines from unmanned aerial vehicle images
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1. Insulator Defect Detection Based on YOLOv5s-KE;Electronics;2024-09-02
2. FishFocusNet: An improved method based on YOLOv8 for underwater tropical fish identification;IET Image Processing;2024-08-07
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