科技创新与应用2025，Vol.15Issue(13)：29-32,4.DOI:10.19981/j.CN23-1581/G3.2025.13.007
基于YOLOv5的消毒机器人目标识别技术研究
李骞 1李军涛 1陈敏 1岳春龙 1刘博1
作者信息
摘要
Abstract
To solve the problems of high computational resources,long processing time,and low recognition accuracy in disinfection robot target recognition technology,a disinfection robot target recognition technology based on YOLOv5 was proposed.This technology mainly uses a novel convolutional neural network(CNN)combined with a machine vision system to achieve detection,classification,and spatial positioning of the targets in the disinfection area required by the disinfection robot.Through real-simulation experiments and detection result analysis on target images in different public scenes,this method can effectively realize the recognition and positioning of disinfection targets.The experimental results show that YOLOv5s and YOLOv5m in the YOLOv5 series are both excellent pre-training models for target detection,and their application scenarios are different.关键词
消毒机器人/目标识别/YOLOv5算法/机器视觉/模型训练Key words
disinfection robot/target recognition/YOLOv5 algorithm/machine vision/model training分类
医药卫生引用本文复制引用
李骞,李军涛,陈敏,岳春龙,刘博..基于YOLOv5的消毒机器人目标识别技术研究[J].科技创新与应用,2025,15(13):29-32,4.
