1Freshta Akhtary,2Engila Akhtary,3Qurban Ali Karimi
1Lecturer at Parwan University, Parwan, Afghanistan
2Lecturer at Kabul University of Medical Sciences Abu Ali Sina
3Epidemiologic Research Specialist
DOI : https://doi.org/10.47191/ijmra/v5-i11-31Google Scholar Download Pdf
ABSTRACT:
Identification of individuals using face masks has become a widespread concern as a result of the coronavirus pandemic. One critical method of preventing pandemic spread is for persons to constantly wear masks in public places. To achieve the maximum possible accuracy, new approaches for face mask detection are being developed that utilize convolutional neural networks. These novel techniques attempt to construct a binary face classifier capable of categorizing pixels in an image as either faces or non faces. In this study, we created a model using Resnet18 and MobileNetv2 in order to obtain trustworthy results for picture categorization. Additionally, we constructed our model for detecting live webcam feeds utilizing Transfer Learning on these deep convolutional neural networks, as well as ImageNet weights and OpenCV.
KEYWORDSFace mask detection, Image classification, MobileNetv2, ResNet18, Semantic segmentation, Transfer learning.
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Volume 05 Issue 11 November 2022
There is an Open Access article, distributed under the term of the Creative Commons Attribution – Non Commercial 4.0 International (CC BY-NC 4.0) (https://creativecommons.org/licenses/by-nc/4.0/), which permits remixing, adapting and building upon the work for non-commercial use, provided the original work is properly cited.
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