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Skin disease classification using deep learning

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dc.contributor.author Remel, Mahinoor Islam
dc.date.accessioned 2024-08-29T06:37:32Z
dc.date.available 2024-08-29T06:37:32Z
dc.date.issued 2024-01-24
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/13263
dc.description.abstract This study presents an in-depth study of the development of Skin Disease Classification using Deep Learning. The dataset was carefully selected to ensure that it was representative of the skin Disease of various kinds: ‘Melanoma’, ‘BCC’, ‘Psoriasis’, and ‘Seborrheic’. EfficientNet B5 with kneeway 3 is being used to classify these diseases, a unique method for reliably and efficiently classifying skin diseases. The high accuracy shows that it has the potential to be used in real-world scenarios, showing its accuracy in identifying various skin diseases detection and accurately verifying those diseases. en_US
dc.publisher Daffodil International University en_US
dc.subject Deep Learning en_US
dc.subject Disease Detection en_US
dc.subject Medical Imaging en_US
dc.subject Dermatology en_US
dc.subject Skin Disease en_US
dc.title Skin disease classification using deep learning en_US
dc.type Other en_US


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