Paper
9 October 2023 Research on infrared insulator image recognition based on improved YOLOv5
Chaoyue Lang, Xiu Ji, Beimin Xie, Hexin Wang, Peng Wu
Author Affiliations +
Proceedings Volume 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023); 1279115 (2023) https://doi.org/10.1117/12.3004899
Event: Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 2023, Qingdao, SD, China
Abstract
As the scale of transmission lines is expanding, the safety of transmission line operation is getting more and more attention; insulators as an important component of transmission lines, the use of insulators greatly affects the safe operation of transmission lines. The traditional depth recognition algorithm can not achieve effective recognition of infrared images, in order to achieve rapid recognition of insulators in complex environments, this paper proposes the recognition of infrared insulator images based on the improved YOLOv5 depth neural network detection algorithm. Firstly, Ghost convolution was introduced into the backbone network to speed up detection and network lightweighting; secondly, to enhance the multi-scale convergence of networks, improved GAM attention module added behind the neck network; in addition, the network introduces an EIOU loss function for convergence; finally, validation of this improved algorithm with the collected infrared insulator dataset. The results show that the improved algorithm in this paper achieves 91.2% accuracy and 92.1% mAP on the infrared insulator dataset, which improves 2.3% and 4.1% compared with the test results of YOLOv5 model, simultaneous detection speed up to 91 FPS, which meets the real-time requirement.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Chaoyue Lang, Xiu Ji, Beimin Xie, Hexin Wang, and Peng Wu "Research on infrared insulator image recognition based on improved YOLOv5", Proc. SPIE 12791, Third International Conference on Advanced Algorithms and Neural Networks (AANN 2023), 1279115 (9 October 2023); https://doi.org/10.1117/12.3004899
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KEYWORDS
Infrared radiation

Infrared imaging

Detection and tracking algorithms

Convolution

Infrared detectors

Neck

Target recognition

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