i-manager Publications

A Survey on Detection of Face Mask and Social Distancing Using Deep Learning

Kavitha Dhanushkodi *, A. Nazer Hussain **, A. Jayaprakash ***, S. Suriyaprakash ****

*-**** Department of Computer Science and Engineering, SRM Valliammai Engineering College, Chennai, Tamil Nadu, India.

Periodicity:March - May'2021
DOI : https://doi.org/10.26634/jit.10.2.18184

World Health Organization : COVID-19 - Global literature on coronavirus disease

https://pesquisa.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/en/covidwho-1631688

ProQuest Central | ID: covidwho-1631688

Abstract

COVID-19, also known as the Corona Virus, caused drastic changes in civilization, eventually leading to a pandemic. Many businesses were affected by the rapidly spreading Corona virus. The focus of this research is on finding a solution to avoid the transit rate. The current research focuses on the many fundamental causes of illness propagation and the technological systems' contributions to disease control. Wearing a facemask and maintaining social distance are two frequent ways to avoid the rapid spread of the disease. To determine whether or not social distancing and face mask protection are being employed, image and video processing are used. In this proposed system, we will see how we may monitor social distancing and implement face mask detection in public areas and workplaces using Python, Computer Vision and Deep Learning.

Keywords

Convolution Neural Networks, COVID-19, Machine Learning, Deep Learning, Social Distancing, Human Detection, Face Detection, Video Processing, Image Processing.

How to Cite this Article?

Dhanushkodi, K., Hussain, A. N., Jayaprakash, A., and Suriyaprakash, S. (2021). A Survey on Detection of Face Mask and Social Distancing Using Deep Learning. i-manager's Journal on Information Technology, 10(2), 22-29. https://doi.org/10.26634/jit.10.2.18184

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