COVID-19-Preventions-Control-System, Face-Mask, And Face-Hand Detection Framework

Authors

  • Dr. S. Sathyalakshmi  Associate Professor, Hindustan Institute of Technology and Science, Kelambakkam, Tamil Nadu, India
  • Medikonda Venkata Leela Krishna  Hindustan Institute of Technology and Science, Kelambakkam, Tamil Nadu, India
  • Phani Vineel Varma  Hindustan Institute of Technology and Science, Kelambakkam, Tamil Nadu, India
  • Inkulu Sujith  Hindustan Institute of Technology and Science, Kelambakkam, Tamil Nadu, India
  • Pelluri Venkata Sai Goutham Aditya  Hindustan Institute of Technology and Science, Kelambakkam, Tamil Nadu, India

Keywords:

Deep Learning, Convolutional Neural Network, Face mask image dataset

Abstract

The end of 2019 witnessed the outbreak of Coronavirus Disease 2019 (COVID-19), which has continued to be the cause of plight for millions of lives and businesses even in 2021. As the world recovers from the pandemic and plans to return to a state of normalcy, there is a wave of anxiety among all individuals, especially those who intend to resume in person activity. Studies have proved that wearing a face mask significantly reduces the risk of viral transmission as well as provides a sense of protection. However, it is not feasible to manually track the implementation of this policy. Technology holds the key here. So we are introducing a system based on deep learning that which can identify the person either wearing a mask properly or not. To implement the process we consider the dataset called MAFA-data which will be trained using Convolution neural network (CNN) along with computer vision.

References

  1. Y. Fang, Y. Nie, and M. Penny, “Transmission dynamics of the covid-19 outbreak and effectiveness of government interventions: A datadriven analysis,”Journal of medical virology, vol. 92, no. 6, pp. 645–659, 2020.
  2. S. Feng, C. Shen, N. Xia, W. Song, M. Fan, and B. J. Cowling, “Rational use of face masks in the covid19pandemic,”The Lancet Respiratory Medicine, 2020.
  3. Z. Wang, G. Wang, B. Huang, Z. Xiong, Q. Hong, H. Wu, P. Yi, K. Jiang, N. Wang, Y. Peiet al., “Masked facerecognition dataset and application,”arXiv preprint arXiv: 2003.09093, 2020.
  4. Z.-Q. Zhao, P. Zheng, S.-t. Xu, and X. Wu, “Object detection with deep learning: A review,”IEEE transactions on neural networks and learning systems, vol. 30, no. 11, pp. 3212–3232, 2019.
  5. A. Kumar, A. Kaur, and M. Kumar, “Face detection techniques: a review,”Artificial Intelligence Review, vol. 52, no. 2, pp. 927–948, 2019.D.-H. Lee, K.-L. Chen, K.-H. Liou, C.-L. Liu, and J.-L. Liu, “Deep learning and control algorithms of direct perception for autonomous driving, 2019.

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

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Published

2022-12-30

Issue

Volume 8, Issue 6, November-December-2022

Section

Research Articles

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Copyright (c) IJSRCSEIT

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

How to Cite

[1]
Dr. S. Sathyalakshmi, Medikonda Venkata Leela Krishna, Phani Vineel Varma, Inkulu Sujith, Pelluri Venkata Sai Goutham Aditya, " COVID-19-Preventions-Control-System, Face-Mask, And Face-Hand Detection Framework" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 6, pp.147-155, November-December-2022.