{"title":"基于深度学习的面罩检测","authors":"Priscilla Whitin, V. Jayasankar","doi":"10.1109/ICTACS56270.2022.9987782","DOIUrl":null,"url":null,"abstract":"The Covid-19 pandemic created a massive impact on various sectors across the globe. Nearly 400 million people have been affected by Covid-19 as of January 2022. Although vaccines have been developed, only 49.8% of world population have been vaccinated. The W.H.O has advised the public to maintain social distance in crowded places and wear well fitted mask to impede the spread of corona virus. It has been made mandatory by most countries to wear mask in public places, human monitoring continuously is impossible hence we deploy Deep learning model to implement the same. In this paper we have trained mobilenetV2 architecture for facemask detection using custom dataset. The accuracy of the model in real time is 99.99%","PeriodicalId":385163,"journal":{"name":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep Learning Based Facemask Detection\",\"authors\":\"Priscilla Whitin, V. Jayasankar\",\"doi\":\"10.1109/ICTACS56270.2022.9987782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Covid-19 pandemic created a massive impact on various sectors across the globe. Nearly 400 million people have been affected by Covid-19 as of January 2022. Although vaccines have been developed, only 49.8% of world population have been vaccinated. The W.H.O has advised the public to maintain social distance in crowded places and wear well fitted mask to impede the spread of corona virus. It has been made mandatory by most countries to wear mask in public places, human monitoring continuously is impossible hence we deploy Deep learning model to implement the same. In this paper we have trained mobilenetV2 architecture for facemask detection using custom dataset. The accuracy of the model in real time is 99.99%\",\"PeriodicalId\":385163,\"journal\":{\"name\":\"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTACS56270.2022.9987782\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTACS56270.2022.9987782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Covid-19 pandemic created a massive impact on various sectors across the globe. Nearly 400 million people have been affected by Covid-19 as of January 2022. Although vaccines have been developed, only 49.8% of world population have been vaccinated. The W.H.O has advised the public to maintain social distance in crowded places and wear well fitted mask to impede the spread of corona virus. It has been made mandatory by most countries to wear mask in public places, human monitoring continuously is impossible hence we deploy Deep learning model to implement the same. In this paper we have trained mobilenetV2 architecture for facemask detection using custom dataset. The accuracy of the model in real time is 99.99%