计算机工程与应用2024，Vol.60Issue(8)：320-328,9.DOI:10.3778/j.issn.1002-8331.2301-0057
自然场景下配电线网施工安全帽佩戴检测算法
Safety Helmet Wearing Detection Algorithm for Distribution Network Construction in Natural Scenarios
摘要
Abstract
For high-risk industries such as distribution network construction operations,wearing safety helmets in accor-dance with safety codes during construction is one of the effective ways to avoid accidents.Due to the complex and changeable construction environment of distribution network,the existing safety helmet identification methods often have the problem of false detection and leakage in natural scenarios and cannot meet the real-time requirements.In order to improve the recognition accuracy and efficiency of safety helmets in natural scenes,a safety helmet wearing recognition detection network model YOLO-ACON-Attention for distribution network construction in natural scenes is proposed.Based on the YOLOv5 algorithm,the adaptive judgment activation function is used to replace the original activation function to strengthen the model detection ability.Secondly,the adaptive attention module is constructed by using the two-round and four-way IRNN network in the backbone network to improve the image information feature extraction ability of the model.Experimental results show that compared with the original YOLOv5 algorithm,the accuracy and recall of the algo-rithm are 94.75%and 89.29%,which are improved by 7.65%and 5.17%,respectively,and the detection speed is 36.5 FPS.关键词
安全帽检测/目标检测/激活函数/注意力网络Key words
helmet detection/object detection/activation function/attention networks分类
信息技术与安全科学引用本文复制引用
许逵,李鑫卓,张历,张俊杰,杨宁..自然场景下配电线网施工安全帽佩戴检测算法[J].计算机工程与应用,2024,60(8):320-328,9.基金项目
中国南方电网科技项目(066600KK52210050). （066600KK52210050）
