A Survey on Deep Learning - Based COVID-19 Safety Monitoring

Steffy Francis; Jensy V

A Survey on Deep Learning - Based COVID-19 Safety Monitoring

June 2021

Vol-7, Issue-3

Paper ID: 14674

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Social distancing Facemask detection Yolo v3 Deep learning Tensorflow

Abstract

COVID-19 caused drastic changes in civilization, eventually leading to a pandemic. Many businesses have remained unaffected by the rapidly spreading Corona virus. Investigate, the focus is on finding a way to avoid the transit rate. The current research is centered on delving into the many fundamental causes of the problem. The spread of disease and the technological systems' contributions keep it under control. Wearing a facemask and maintaining social distance are two basic ways to avoid transit right away. Deep learning technologies are examples of such technologies. Assisting developers in the analysis of publically available data such as X-rays, CT scans, and text data from numerous conversations in social media, and so on. To determine whether or not social distancing and face mask protection are being monitored, image and video processing are used. The connection of CCTV cameras in the Public areas, public transportation, and hospitals are useful for gathering information. In this survey paper We will discuss about the technologies used for this in detail.

License

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Author Information

#	Name	Institute / Affiliation
1	Steffy Francis	IES College of Engineering Chittilappilly
2	Jensy V	IES College of Engineering Chittilappilly

How to Cite

Use the following formats to cite this article in your research.

APA Style

Francis, Steffy & V, Jensy (2021). A Survey on Deep Learning - Based COVID-19 Safety Monitoring. International Journal of Advance Research and Innovative Ideas In Education, 7(3), 2783-2787.

MLA Style

Francis, Steffy, and Jensy V. "A Survey on Deep Learning - Based COVID-19 Safety Monitoring." International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, 2021, pp. 2783-2787.

IEEE Style

Steffy Francis and Jensy V, "A Survey on Deep Learning - Based COVID-19 Safety Monitoring," International Journal of Advance Research and Innovative Ideas In Education, vol. 7, no. 3, pp. 2783-2787, 2021.

Vancouver Style

Francis Steffy, V Jensy. A Survey on Deep Learning - Based COVID-19 Safety Monitoring. International Journal of Advance Research and Innovative Ideas In Education. 2021;7(3):2783-2787.

Harvard Style

Francis, Steffy & V, Jensy (2021) 'A Survey on Deep Learning - Based COVID-19 Safety Monitoring', International Journal of Advance Research and Innovative Ideas In Education, 7(3), pp. 2783-2787.

Chicago Style

Francis, Steffy and Jensy V. "A Survey on Deep Learning - Based COVID-19 Safety Monitoring." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 2783-2787.

Turabian Style

Francis, Steffy and Jensy V. "A Survey on Deep Learning - Based COVID-19 Safety Monitoring." International Journal of Advance Research and Innovative Ideas In Education 7, no. 3 (2021): 2783-2787.