Facial Mask Detection Using Transfer Learning with Resnet18 and MobileNetV2

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.

Authors and Affiliations

Freshta Akhtary, Engila Akhtary, Qurban Ali Karimi

Keywords

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  • EP ID EP712848
  • DOI 10.47191/ijmra/v5-i11-31
  • Views 161
  • Downloads 0

How To Cite

Freshta Akhtary, Engila Akhtary, Qurban Ali Karimi (2022). Facial Mask Detection Using Transfer Learning with Resnet18 and MobileNetV2. International Journal of Multidisciplinary Research and Analysis, 5(11), -. https://europub.co.uk/articles/-A-712848