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Monkeypox Detection using MobileNetV2.

Authors :
Thanawala, Aniket Sejal
Ujjainwala, Abdul Qadir
Barot, Kanaiya Manek
Rathod, Krishna Sanjay
Devmane, Vidyullata
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