图像识别技术在实验室防疫中的应用研究  

Research on the application of image recognition technology in laboratory epidemic prevention

作　　者：季瑞松[1] 张建良[1] 吴云杰 JI Ruisong;ZHANG Jianliang;WU Yunjie(College of Electrical Engineering,Zhejiang University,Hangzhou 310012,China;Zhejiang Dahua Technology CO.,LTD,Hangzhou 310051,China)

机构地区：[1]浙江大学电气工程学院,浙江杭州310012 [2]浙江大华技术股份有限公司,浙江杭州310051

出　　处：《实验室科学》2022年第6期44-47,共4页Laboratory Science

基　　金：浙江大学实验技术研究项目(项目编号:SJS201803)。

摘　　要：佩戴口罩是最有效的阻断病毒传播的方法。高校实验室是重要的教学和科研场所,在新冠疫情防控常态化形势下,口罩的佩戴非常关键。利用安装在实验室中的监控相机,对实验室人员的口罩佩戴情况进行实时智能识别,将有效提升实验室人员佩戴口罩的意识。YOLOv3网络是非常有效的目标检测算法。对该网络进行了改进,使之能有效应用于实验室环境下的口罩检测。Wearing a mask is the most effective way to block the spread of the virus. Laboratories are important teaching and research places in the university. Preventing the spread of COVID-19 will be a normal state for a long time, so the wearing of masks is very important. The real-time intelligent recognition of the mask wearing will effectively enhance the consciousness of wearing masks for students and teachers with the help of camera installed in the laboratory. YOLOv3 network is a very effective target detection algorithm. In this paper, the network has been improved so that it can be effectively used for mask detection in laboratory environment.

关 键 词：口罩 智能识别 YOLOv3网络 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]