Open AccessDeep Learning Approach for detecting Covid-19 Face mask using YOLOv4 Algorithm
Author(s) -
Rutuja R. Mahurkar,
Naresh G. Gadge
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit2172122
Subject(s) - covid-19 , face (sociological concept) , computer science , artificial intelligence , transmission (telecommunications) , deep learning , face masks , computer vision , pandemic , object (grammar) , face detection , pattern recognition (psychology) , facial recognition system , telecommunications , virology , medicine , social science , disease , pathology , sociology , outbreak , infectious disease (medical specialty)
The Covid-19 is declared a pandemic all over the world by WHO on 11 March 2020. Various guidelines were issued by WHO for the prevention of coronavirus. One of the guidelines is wearing a face mask. From the various researches, it is proven that wearing a face mask minimizes the risk of virus transmission. Thus, a system is needed which reduces the load on governing body in the accomplishment of Covid-19 laws in crowded public places. A deep learning model using the YOLOv4 object detection algorithm is used for detecting whether people are wearing a mask or not, from images and video streams. In the proposed methodology, CSPDarknet53 is used for extracting facial mask features.