Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/14972
Title: Facemask Detection System Using CNN Model
Authors: Senbagavalli, M
Debnath, Saswati
Rajagopal, R
Ghildial, Kishkind
Keywords: Cnn
Face Mask Detection
Opencv
Single Shot Multi-Box Detector
Yolo
Issue Date: 2023
Publisher: International Conference on Recent Advances in Science and Engineering Technology, ICRASET 2023
Institute of Electrical and Electronics Engineers Inc.
Abstract: Global 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.
URI: https://doi.org/10.1109/ICRASET59632.2023.10420345
http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/14972
ISBN: 9.79835E+12
Appears in Collections:Conference Papers

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