Skin disease classification using deep learning

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