The accuracy of traditional personnel safety behavior identification method is low.To solve this problem,the study proposes a method for personnel safety behavior identification in thermal power plant based on YOLOv5 algorithm,classifies and labels personnel safety behaviors,constructs data sets which is suitable for thermal power plant scenarios and a multi-target detection model by feature extraction and matching algorithms combined with YOLOv5 algorithm.It can reliably detect and identify all kinds of security behaviors.The experimental results show that this method can effectively identify personnel safety behavior in the thermal power plant scene,and provide reliable auxiliary means for personnel safety management.
关键词
YOLOv5算法/特征提取/匹配算法/目标检测模型
Key words
YOLOv5 algorithm/Feature extraction/Matching algorithm/Target detection model
维普
万方数据