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Machine learning based human body temperature measurement and mask detection by thermal imaging
3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022 ; : 1339-1343, 2022.
Article in English | Scopus | ID: covidwho-2136267
ABSTRACT
The worldwide impact of the COVID-19 epidemic has been immense. Economic, educational, industrial, and other sectors all took a hit as a result of COVID-19. Unaware of how to address this, the health care industry was also hit. In the absence of a known cure, the most effective way to slow the spread of this fatal illness is to wear a face mask when doing so. Wearing a face mask when in public or conversing with people is also mandated by the WHO. Additionally, the most common symptom is high fever, which occurs in those who are unwell with this condition. As a result, we describe a system that can distinguish face masks using a regular RGB camera and identify persons with high body temperatures using a thermal camera with an 80x60 resolution. Tracking safety violations and encouraging the use of face masks may be achieved by using this method. © 2022 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 3rd International Conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022 Year: 2022 Document Type: Article