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Nail Disease Identification and Treatment Recommendation System

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dc.contributor.author Dahanayake, Yeheni
dc.date.accessioned 2024-03-29T07:16:16Z
dc.date.available 2024-03-29T07:16:16Z
dc.date.issued 2023
dc.identifier.citation Dahanayake, Yeheni (2023) Nail Disease Identification and Treatment Recommendation System. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20191054
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1948
dc.description.abstract "Nail fungus detection using image processing is a cutting-edge method for determining whether there is nail fungus present. Millions of people worldwide suffer from the widespread condition of nail fungus, which can be extremely uncomfortable and raise aesthetic issues. Visual inspection is the conventional way for identifying nail fungus, however this is frequently subjective and unreliable. The author has used image processing methods, notably Convolutional Neural Networks (CNNs) coupled with a residual architecture, to get around this restriction. To achieve this, the author performed picture augmentations to construct a dataset." en_US
dc.language.iso en en_US
dc.publisher en_US
dc.subject Image Processing en_US
dc.subject Nail Fungus Detection en_US
dc.subject Convolutional Neural Networks en_US
dc.title Nail Disease Identification and Treatment Recommendation System en_US
dc.type Thesis en_US


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