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一种使用卷积神经网络的实时口罩检测系统。

A real time face mask detection system using convolutional neural network.

作者信息

Goyal Hiten, Sidana Karanveer, Singh Charanjeet, Jain Abhilasha, Jindal Swati

机构信息

Department of Computer Science and Engineering, Maharaja Ranjit Singh Punjab Technical University, Bathinda, India.

出版信息

Multimed Tools Appl. 2022;81(11):14999-15015. doi: 10.1007/s11042-022-12166-x. Epub 2022 Feb 25.

DOI:10.1007/s11042-022-12166-x
PMID:35233179
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8874748/
Abstract

In current times, after the rapid expansion and spread of the COVID-19 outbreak globally, people have experienced severe disruption to their daily lives. One idea to manage the outbreak is to enforce people wear a face mask in public places. Therefore, automated and efficient face detection methods are essential for such enforcement. In this paper, a face mask detection model for static and real time videos has been presented which classifies the images as "with mask" and "without mask". The model is trained and evaluated using the Kaggle data-set. The gathered data-set comprises approximately about 4,000 pictures and attained a performance accuracy rate of 98%. The proposed model is computationally efficient and precise as compared to DenseNet-121, MobileNet-V2, VGG-19, and Inception-V3. This work can be utilized as a digitized scanning tool in schools, hospitals, banks, and airports, and many other public or commercial locations.

摘要

当前，在新冠疫情在全球迅速蔓延之后，人们的日常生活受到了严重干扰。应对疫情的一个办法是强制人们在公共场所佩戴口罩。因此，自动化且高效的面部检测方法对于这种强制要求至关重要。本文提出了一种用于静态和实时视频的口罩检测模型，该模型将图像分类为“戴口罩”和“未戴口罩”。该模型使用Kaggle数据集进行训练和评估。收集的数据集包含大约4000张图片，性能准确率达到了98%。与DenseNet - 121、MobileNet - V2、VGG - 19和Inception - V3相比，所提出的模型计算效率高且精确。这项工作可以用作学校、医院、银行、机场以及许多其他公共或商业场所的数字化扫描工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f0/8874748/c2ec23ec4b04/11042_2022_12166_Fig10_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f0/8874748/e86e70ee6402/11042_2022_12166_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f0/8874748/b8e06693b9bd/11042_2022_12166_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94f0/8874748/01d835c0a59e/11042_2022_12166_Fig9_HTML.jpg
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Identifying Facemask-Wearing Condition Using Image Super-Resolution with Classification Network to Prevent COVID-19.利用图像超分辨率和分类网络识别口罩佩戴状态，预防 COVID-19。
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