Design and Implementation of Glove Standard Wear Detection System Based on Deep Learning
In order to solve the problem of poor environmental adaptability of the existing glove detection technology and the inability to detect whether the operator wears gloves standardly,a glove standard wearing detection system based on deep learning object detection technology was developed.Firstly,combined with the requirements of standardized wearing of gloves in industrial sites,the overall design scheme of the standardized wearing detection system of gloves was proposed,and the detection process of the system was given.Secondly,an improved YOLOv4-DN-CM object detection algorithm based on YOLOv4 was proposed,which could increase the detection speed by 43.4％without reducing the detection accuracy.Finally,based on the relevant software and hardware,the standard wearing detection system of gloves was developed,and the standard wearing detection experiment of grinding machine gloves was carried out.The experimental re-sults show that the glove standard wearing detection system based on deep learning can efficiently detect the standard wearing of gloves by workers and reduce the occurrence of hand safety accidents.
Deep learningYOLOv4Glove wear detectionHuman detection
NETL
NSTL
万方数据
