Infrared Image Recognition System for Substation Equipment Based on Improved YOLOv7-Tiny Technology
The original YOLOv7-Tiny faces the problems of insufficient recognition accuracy and slow processing speed when processing infrared images of substation equipment.To address these issues,a new model adjustment strategy was introduced and the performance of the algorithm before and after improvement was compared on a standard infrared image dataset.The results show that the improved YOLOv7-Tiny has significantly improved recognition accuracy and efficiency.By targeted optimization of YOLOv7-Tiny,the fault detection capability of infrared images of substation equipment can be significantly improved,providing more reliable technical support for the stable operation of the power system.
improved YOLOv7-Tiny technologysubstation equipmentinfrared image recognition system
NETL
NSTL
万方数据
