Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments

S. VELUCHAMY 1
, 
Rajeesh Kumar N V 2
, 
P. Srinivasan 3
, 
Nandhakumar A 4
, 
K. G. Parthiban 4
1
 
Department of Electronics and Communication Engineering, Sri Venkadeswara College of Engineering and Technology, Coimbatore, India | 
2
 
Computer Science and Engineering, Amrita College of Engineering and Technology, Coimbatore, India | 
3
 
Department of Electronics and Communication Engineering, Amrita College of Engineering and Technology, Coimbatore, India | 
4
 
Department of Electronics and Communication Engineering, Dhaanish Ahmed Institute of Technology, Coimbatore, India | 
Publication type: Book Chapter
Publication date: 2024-07-09
Bentham Science Publishers Ltd.
SJR: —
CiteScore: —
Impact factor: —
ISSN: 30292859
Abstract

The number of people using face masks has increased on public transportation, retail outlets, and at the workplace. All municipal entrances, workplaces, malls, schools, and hospital gates must have temperature and mask checks in order for people to enter. The paper's goal is to find someone who isn't wearing a face mask in order to control COVID-19. ConvNets may be used to recognize and classify images. The model depends on ConvNot to assess whether or not someone is wearing a mask. It is possible to identify an image's face by utilizing a face identification algorithm. These faces are then processed using Conv Net face mask detection. If the model is able to extract patterns and characteristics from photographs, it will be categorized as either “Mask” or “No Mask”. With an accuracy rate of 99.85 percent, Mobile Net V2 is the most accurate in regard to training data. MobilenetV2 correctly identifies the mask in “Mask” or “No Mask” video transmissions.<br>

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VELUCHAMY S. et al. Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments // Advanced Technologies for Science and Engineering. 2024. pp. 50-66.
GOST all authors (up to 50) Copy
VELUCHAMY S., N V R. K., Srinivasan P., A N., Parthiban K. G. Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments // Advanced Technologies for Science and Engineering. 2024. pp. 50-66.
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RIS Copy
TY - GENERIC
DO - 10.2174/9789815196269124030006
UR - https://www.eurekaselect.com/node/231800
TI - Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments
T2 - Advanced Technologies for Science and Engineering
AU - VELUCHAMY, S.
AU - N V, Rajeesh Kumar
AU - Srinivasan, P.
AU - A, Nandhakumar
AU - Parthiban, K. G.
PY - 2024
DA - 2024/07/09
PB - Bentham Science Publishers Ltd.
SP - 50-66
SN - 3029-2859
ER -
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Cite this
BibTex (up to 50 authors) Copy
@incollection{2024_VELUCHAMY,
author = {S. VELUCHAMY and Rajeesh Kumar N V and P. Srinivasan and Nandhakumar A and K. G. Parthiban},
title = {Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments},
publisher = {Bentham Science Publishers Ltd.},
year = {2024},
pages = {50--66},
month = {jul}
}