Computer Vision and Machine Learning-Based Techniques for Detecting the Safety Violations of COVID-19 Scenarios: A Review
5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC)
; 1420:239-251, 2021.
Article
in English
| Web of Science | ID: covidwho-1819414
ABSTRACT
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus2. COVID-19 has created the worldwide pandemic situation and it is causing a greater health crisis and deaths of the millions of humans all over the world. All the socio-economic activities are very much affected and there is a huge loss over the world in many aspects. If safety measures are not followed strictly in the public places, then there is a rapid spread of the disese at a very faster rate. Hence, this paper provides a thorough survey of the existing computer vision and machine learning-based technological solutions for controlling the spread of the disease. It also discusses some challenges and future perspectives in developing systems for monitoring the COVID-19 safety violations.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Language:
English
Journal:
5th International Conference on Computational Vision and Bio Inspired Computing (ICCVBIC)
Year:
2021
Document Type:
Article
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