计算机与数字工程2025，Vol.53Issue(2)：415-421,485,8.DOI:10.3969/j.issn.1672-9722.2025.02.020
基于改进YoloX的输电通道工程车辆小目标检测识别
Detection and Recognition of Small Targets of Vehicles in Transmission Channel Based on Improved YoloX
摘要
Abstract
In view of the phenomenon that small targets of engineering vehicles under the transmission channel seriously threaten the safety of the transmission channel,and the original YoloX algorithm has seriously missed the detection of small targets,the visual attention mechanism SK is added to the original single-stage target detection algorithm YoloX to increase the receptive field.The hole convolution module is used to replace the SPP module in the original network to further fuse different receptive field information.ASFF module is added in the network Neck part to improve the fine-grained features in the underlying features.Final-ly,the second recognition post-processing method is used to further reduce the miss detection rate of small targets.The experimen-tal results show that the proposed algorithm improves the detection accuracy.Compared with the traditional YoloX algorithm,the map is improved by 8.46%,and the recognition effect of small targets is significantly improved,which proves the effectiveness of the new algorithm.关键词
YoloX/小目标/注意力机制/ASFF/二次识别Key words
YoloX/small targets/attention mechanism/ASFF/secondary identification分类
信息技术与安全科学引用本文复制引用
张智坚,焦良葆,高阳,邹辉军,孙宏伟,王彦生..基于改进YoloX的输电通道工程车辆小目标检测识别[J].计算机与数字工程,2025,53(2):415-421,485,8.基金项目
江苏省自然科学基金项目(编号:BK20201042)资助. （编号:BK20201042）
