Research on transmission line identification technology under YOLOv5 framework

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.