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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.
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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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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