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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 4, APRIL 2021

Analysis of Face Mask Detection Techniques

Dr. Prakash Prasad, Mukul Shende, Amit Dravyakar, Mayur Karemore, Lucky Khobragade, Davesh Bondre

DOI: 10.17148/IJARCCE.2021.10472

Abstract: The world is experiencing severe health issue as a result of the rapid spread of coronavirus disease-2019 (COVID-19). According to the World Health Organization (WHO), the best way to prevent the spread of COVID-19 is wearing a mask and keeping a distance. But there is huge neglect of the guidelines by people which is resulting in daily increase in an infected patient. In these regions, manually monitoring the citizens is quite challenging. So, in this paper, we study ideas to monitor people using the automation process to identify the people who are wearing the mask and who are not. Many incipient trained models are being developed utilizing pre-subsisting datasets to make the algorithm as precise as possible.

Keywords: Semantic Segmentation, OpenCV, Convolutional Neural Network(CNN), YOLO, Deep Learning,

How to Cite:

[1] Dr. Prakash Prasad, Mukul Shende, Amit Dravyakar, Mayur Karemore, Lucky Khobragade, Davesh Bondre, “Analysis of Face Mask Detection Techniques,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10472