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Monkeypox Detection using MobileNetV2.
- Source :
- Grenze International Journal of Engineering & Technology (GIJET); Jan Part 2, Vol. 10, p1269-1273, 5p
- Publication Year :
- 2024
-
Abstract
- With the worldwide decline in COVID-19 viral infections, the monkeypox virus is slowly returning. People are scared of it because they believe that it will spread like COVID-19. As a result, it is essential to find them sooner than they spread widely within the community. The early discovery of them might be made possible by ML-based detection. Public health is endangered by the swift spread of the monkeypox outbreak to over 40 nations beyond Africa. Monkeypox is challenging to diagnose at an early stage since it shares similarities with both chickenpox and measles. To monitor and identify potential cases promptly, computer-assisted detection of monkeypox lesions could be helpful in situations where PCR tests for confirmation are not readily available. Provided that there are adequate training samples, deep learning methods have demonstrated effectiveness in automatically identifying skin lesions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 23955287
- Volume :
- 10
- Database :
- Complementary Index
- Journal :
- Grenze International Journal of Engineering & Technology (GIJET)
- Publication Type :
- Academic Journal
- Accession number :
- 175658243