软件导刊2024，Vol.23Issue(1)：135-142,8.DOI:10.11907/rjdk.231683
基于混合注意力机制与C2f的行人检测算法研究
Research on Pedestrian Detection Algorithm Based on Mixed Attention Mechanism and C2f
摘要
Abstract
Aiming at the problems of missing detection and false detection of small target pedestrians with small scale and dense pedestrians,this paper proposes a pedestrian detection algorithm with mixed attention mechanism and C2f module based on YoloX algorithm.In this algo-rithm,firstly,the BAM module and the C2f module are fused to effectively enhance the characteristics of pedestrians,reduce the amount of calculation,and improve the detection speed.Secondly,the attention mechanism is used to guide the network to pay attention to pedestrian tar-gets,and the characteristic information of pedestrian targets has been further strengthened.Finally,experimental analysis is carried out on the Crowd Human dataset,when the IoU threshold is set to 0.5,the small-scale pedestrian detection accuracy is 21.1%,the mesoscale pedestrian detection accuracy is 47.3%,the large-scale pedestrian detection accuracy is 64.7%,the total pedestrian target detection accuracy is 73.2%,and the detection speed is 24.3 frames per second.Experimental results show that the pedestrian detection algorithm in this paper effectively improves the detection accuracy and detection speed of pedestrian targets,and has good detection performance for pedestrian targets.关键词
行人检测/特征增强/YoloX/深度学习/注意力机制Key words
pedestrian detection/feature enhancement/YoloX/deep learning/attention mechanisms分类
计算机与自动化引用本文复制引用
王志新,王如刚,王媛媛,周锋,郭乃宏..基于混合注意力机制与C2f的行人检测算法研究[J].软件导刊,2024,23(1):135-142,8.基金项目
国家自然科学基金项目(61673108) （61673108）
江苏省研究生实践创新计划项目(SJCX22_1685,SJCX21_1517) （SJCX22_1685,SJCX21_1517）
江苏省高等学校自然科学研究重大项目(19KJA110002) （19KJA110002）
江苏省高校自然科学研究面上项目(18KJD510010,19KJB510061) （18KJD510010,19KJB510061）
江苏省自然科学基金项目(BK20181050) （BK20181050）
