Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14972
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dc.contributor.authorSenbagavalli, M-
dc.contributor.authorDebnath, Saswati-
dc.contributor.authorRajagopal, R-
dc.contributor.authorGhildial, Kishkind-
dc.date.accessioned2024-03-30T10:11:00Z-
dc.date.available2024-03-30T10:11:00Z-
dc.date.issued2023-
dc.identifier.isbn9.79835E+12-
dc.identifier.urihttps://doi.org/10.1109/ICRASET59632.2023.10420345-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14972-
dc.description.abstractGlobal trade and transportation have been impacted by the COVID-19 epidemic, which has quickly affected our everyday activities. One of the best ways to stop the Covid-19 virus from transmitting is to wear a face mask. As a result, the World Health Organization (WHO) advised wearing masks as a precaution in crowded areas. Not only COVID-19, wearing mask can reduce the risk of many infectious diseases. In certain places, diseases caused by bacteria, viruses, fungi, or parasites spread quickly due to the inappropriate usage of face masks. Many public services providers demand that their clientele participate in their services while suitably dressed in masks. Therefore, identifying face masks has become a crucial duty in supporting global civilization. This paper develops face mask detection system with an alert that detects the presence of a mask in real-time. The proposed system accurately examines the face from the picture and then determines whether it is covered by a mask or not. A notification can be issued to the administrator if the camera records an unrecognizable face. After that, the administrator will be able to track down the infringer. © 2023 IEEE.en_US
dc.language.isoenen_US
dc.publisherInternational Conference on Recent Advances in Science and Engineering Technology, ICRASET 2023en_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.subjectCnnen_US
dc.subjectFace Mask Detectionen_US
dc.subjectOpencven_US
dc.subjectSingle Shot Multi-Box Detectoren_US
dc.subjectYoloen_US
dc.titleFacemask Detection System Using CNN Modelen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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