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Skin Diseases Detection System for Diagnosis of Eczema, Psoriasis and Tinea

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dc.contributor.author Liyana Gunawardhana, Wasura
dc.date.accessioned 2022-12-19T04:33:23Z
dc.date.available 2022-12-19T04:33:23Z
dc.date.issued 2022
dc.identifier.citation Liyana Gunawardhana, Wasura (2022) Skin Diseases Detection System for Diagnosis of Eczema, Psoriasis and Tinea. BEng. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2017191
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1151
dc.description.abstract Psoriasis, Eczema and Tinea Ringworm are widespread degenerative skin diseases that has a high sensitivity in diagnosing. Early detection, which is essential for a proper diagnosis, demands for the involvement of competent dermatologists and requires a lot of time and effort. It is a challenge in regions where access to specialized healthcare is frequently limited. Additionally, it has the likely to result in a misdiagnosis, unlike computer-assisted diagnostic techniques. Deep learning has recently emerged as one of the best techniques for improving the reliability of medical imaging and classification. In the evaluation of medical images, convolutional neural networks are a more widely accepted and highly effective deep learning technique. This research examined and addressed Psoriasis, Eczema, Tinea Ringworm skin diseases related image classification and detection strategies using deep learning and machine learning approaches. Numerous difficult problems that require more research are highlighted as well. en_US
dc.language.iso en en_US
dc.subject Transfer Learning en_US
dc.subject Neural networks en_US
dc.subject Image processing en_US
dc.subject Skin Diseases Detection en_US
dc.title Skin Diseases Detection System for Diagnosis of Eczema, Psoriasis and Tinea en_US
dc.type Thesis en_US


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