Manuscript Number : CSEIT1217519
Face Mask Recognition Using MobileNetV2
Authors(2) :-Vatsal Patel, Dhruti Patel The pandemic of Corona Virus Disease is generating a public health emergency. Wearing a mask is one of the most efficient ways to combat the infection. This paper presents the detection of face masks, through mitigating, evaluating, preventing, and preparing actions regarding COVID-19. In this work, face mask identification is achieved using Machine Learning technique and the Image Classification algorithms are MobileNetV2 with major changes which includes Label Binarizer, ImageNet, and Binary Cross-Entropy. The methods involved in building the model are collecting the data, pre-processing, image generation, model construction, compilation, and finally testing. The proposed method can recognize people with and without masks. The training accuracy of the proposed method is 98.5% and the testing accuracy is 99%. This model is implemented in an image or video stream to detect faces with mask.
Vatsal Patel Deep Learning, CNN, MobileNetV2, Face Mask, COVID-19 Publication Details Published in : Volume 7 | Issue 5 | September-October 2021 Article Preview
Devang Patel Institute of Advance Technology and Research, Charusat University, Gujarat, India
Dhruti Patel
Devang Patel Institute of Advance Technology and Research, Charusat University, Gujarat, India
Date of Publication : 2021-10-30
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 35-42
Manuscript Number : CSEIT1217519
Publisher : Technoscience Academy
Journal URL : https://res.ijsrcseit.com/CSEIT1217519
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