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Research Article

Face Mask Detection

Open Access Peer Reviewed

Authors

  • Mohammad Anas1
  • Md Sadab Ahmad2
  • Rajkishore Yadav3

12Students, Department of Computer Science and Engineering, Institute of Technology and Management, Gorakhpur Uttar Pradesh, India. 3Asst. Professor, Department of Computer Science and Engineering, Institute of Technology and Management, Gorakhpur, Uttar Pradesh, India.

Article Information

DOI
No DOI
Published Online
March-April 2022
Pages
40-44
Article Type
Research Article
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No DOI available for cross-reference

Abstract

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Abstract: The new Coronavirus disease (COVID-19) has seriously affected the world. By the end of November 2021, the global number of new coronavirus cases had already exceeded 29.9 cr and the number of deaths 45,50,000 according to information from the World Health Organization (WHO). To limit the spread of the disease, mandatory face-mask rules are now becoming common in public settings around the world. Additionally, many public service providers require customers to wear face masks in accordance with predefined rules (e.g., covering both mouth and nose) when using public services. These developments inspired research into automatic (computer-vision-based) techniques for face-mask detection that can help monitor public behavior and contribute towards constraining the COVID-19 pandemic. Although existing research in this area resulted in inefficient techniques for face-mask detection, these usually operate under the assumption that modern face detectors provide perfect detection performance (even for masked faces) and that the main goal of the techniques is to detect the presence of face-masks only.

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