现代信息科技2024，Vol.8Issue(10)：60-63,67,5.DOI:10.19850/j.cnki.2096-4706.2024.10.013
基于改进YOLOv5的电工着装检测方法研究
Research on Electrician Dressing Inspection Method Based on Improved YOLOv5
摘要
Abstract
This paper proposes a dressing detection method based on improved YOLOv5 to address the issue of non-standard dressing among working personnel in hydroelectric power plants.This method uses object detection technology to automatically detect whether working personnel are wearing safety helmets and their work clothes are wearing properly.For small object detection such as helmets,a lightweight ECAnet attention mechanism module is embedded on the basis of the YOLOv5 network model to reduce the computational complexity of useless information channels,while ensuring the advantage of YOLOv5 detection speed,the ability to extract small object features is improved.The results show that the accuracy,recall,and mAP@0.5 of the improved module increased by 4.3%,2.1%,and 1.4%respectively.关键词
目标检测/着装识别/YOLOv5s/注意力机制Key words
target detection/dressing recognition/YOLOv5s/Attention Mechanism分类
信息技术与安全科学引用本文复制引用
李恭乐..基于改进YOLOv5的电工着装检测方法研究[J].现代信息科技,2024,8(10):60-63,67,5.
