Deep Learning Approach for detecting Covid-19 Face mask using YOLOv4 Algorithm

Authors

  • Rutuja R. Mahurkar  Master of Technology Scholar, CSE, GCOE, Amravati, Amravati, Maharashtra, India
  • Prof. Naresh G. Gadge  Assistant Professor, Computer Science and Engineering, GCOE, Amravati, Amravati, Maharashtra, India

DOI:

https://doi.org/10.32628/CSEIT2172122

Keywords:

COVID-19, WHO, YOLOv4, deep learning, CSPDarknet53, Face mask.

Abstract

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.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2021-04-30

Issue

Volume 7, Issue 2, March-April-2021

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Rutuja R. Mahurkar, Prof. Naresh G. Gadge, " Deep Learning Approach for detecting Covid-19 Face mask using YOLOv4 Algorithm" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 2, pp.650-654, March-April-2021. Available at doi : https://doi.org/10.32628/CSEIT2172122