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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 10, ISSUE 6, JUNE 2021

Covid19 Social Distancing Tracker

Amruta Sanjay Chaher, Madhura Arun Darekar, Pratiksha Dhanaji Kadam, Mahendra Nenaram Choudhary, Prof. Sheetal Bhagwat

DOI: 10.17148/IJARCCE.2021.10634

Abstract: COVID-19 has brought global crisis with its deadly spread. In the fight against the coronavirus, social distancing has proven to be a very effective measure to slow down the spread of the disease. India's government is promising to vaccinate the whole of the adult population by the end of 2021, although it’s biggest vaccine maker has been struggling to meet demand as there is shortage of raw materials therefore, social distancing is thought to be an adequate precaution (norm) against the spread of the pandemic virus. This deep learning based framework is used for automating the task of monitoring social distancing. The framework uses the YOLOv3 object recognition paradigm to identify humans in video sequences.

Keywords: COVID, social distancing, YOLO.

How to Cite:

[1] Amruta Sanjay Chaher, Madhura Arun Darekar, Pratiksha Dhanaji Kadam, Mahendra Nenaram Choudhary, Prof. Sheetal Bhagwat, “Covid19 Social Distancing Tracker,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2021.10634