Research on transmission line identification technology under YOLOv5 framework

Jinwei Hao

doi:10.1117/12.3042469

29 August 2024 Research on transmission line identification technology under YOLOv5 framework

Jinwei Hao

Proceedings Volume 13249, International Conference on Computer Vision, Robotics, and Automation Engineering (CRAE 2024); 132490X (2024) https://doi.org/10.1117/12.3042469
Event: 2024 International Conference on Computer Vision, Robotics and Automation Engineering, 2024, Kunming, China

Abstract

This study is dedicated to the in-depth exploration and optimization of transmission line recognition technology using the algorithmic framework of YOLOv5. YOLOv5, as an advanced real-time target detection algorithm, possesses excellent speed and accuracy, and thus has great potential for application in the field of transmission line recognition. First, we construct a transmission line recognition model based on YOLOv5. The model makes full use of the efficiency and accuracy of the YOLOv5 algorithm, and realizes the accurate recognition of transmission lines by training and learning from a large number of transmission line images. Second, in terms of practical application, we developed a transmission line recognition system based on the trained model. The system is able to monitor and recognize transmission lines in real time and discover potential safety hazards and faults in time. Through testing and application in real scenarios, we verified the effectiveness and reliability of the system.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinwei Hao "Research on transmission line identification technology under YOLOv5 framework", Proc. SPIE 13249, International Conference on Computer Vision, Robotics, and Automation Engineering (CRAE 2024), 132490X (29 August 2024); https://doi.org/10.1117/12.3042469

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