Detection of Face Mask Using Deep Learning
B. Prasanna Kumar, B. Chaitanya, B. Rana Prathap Singh, V. Siva, Ch. Jayanth, M. Hanumantharao
Face Mask, Covid-19, Convolutional Neural Networks, Deep learning, Mobile Net V2, Twitter.
Today the biggest problem the world is facing above all the natural disasters is the Covid-19. It's been more than a year but the solution to the issue is still at a far fetch. However, we still have few ways to control the outbreak as instructed by the WHO (World Health Organization). A few among them are wearing a mask and maintaining social distance. The objective of the paper is to detect face masks in a public gathering or an event. The algorithm used in this paper to achieve the objective is MobileNet V2. An image of a few people wearing a mask and without wearing a mask is used as an input dataset. The proposed process includes dataset pre-processing, data augmentation, training, testing and image segmentation. With the help of the Mask R-CNN algorithm, will get a segmented image of the input dataset of people wearing a mask and people not wearing a mask. The proposed algorithm can be merged with real time applications at airports, railway stations, workplaces, schools, and other public places to ensure compliance with the guidelines for public safety.
Article Details
Unique Paper ID: 155414

Publication Volume & Issue: Volume 9, Issue 1

Page(s): 698 - 701
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