机械制造与自动化2024，Vol.53Issue(4)：219-223,229,6.DOI:10.19344/j.cnki.issn1671-5276.2024.04.042
基于改进YOLOv8的电梯内电动车识别方法研究
Research on Identification Method of Electric Vehicles in Elevators Based on Improved YOLOv8
摘要
Abstract
A new electric vehicle identification method combining AUGMIX and improved YOLOv8 model is proposed to address the issues of low efficiency and poor accuracy in identifying electric vehicles in elevators.The YOLOv8 model incorporates DCNv3 and BRA to identify electric vehicles with better accuracy and efficiency.The experimental results show that the precision,recall,and mean average precision of the improved algorithm model reach 94.5%,93%,and 82.4%respectively.And the accuracy of electric vehicle identification reaches 95.8%,providing a theoretical basis for intelligent recognition of electric vehicles in elevators.关键词
电动车识别/AUGMIX/YOLOv8/变形卷积层/动态稀疏注意力机制Key words
machine vision/AUGMIX/YOLOv8/DCNv3/Bi-level routing attention分类
信息技术与安全科学引用本文复制引用
路成龙,冯月贵,庆光蔚..基于改进YOLOv8的电梯内电动车识别方法研究[J].机械制造与自动化,2024,53(4):219-223,229,6.基金项目
国家市场监督管理总局科技计划项目(2022MK156) （2022MK156）
江苏省市场监督管理局科技计划项目(KJ2023039) （KJ2023039）
