Research Directions for Skin Disease Identification Using Image Processing and Machine Learning
dc.contributor.author | Wijesinghe | |
dc.contributor.author | LAN | |
dc.contributor.author | Kulasekera | |
dc.contributor.author | DMR | |
dc.contributor.author | Ilmini | |
dc.contributor.author | WMKS | |
dc.date.accessioned | 2019-11-22T12:44:15Z | |
dc.date.available | 2019-11-22T12:44:15Z | |
dc.date.issued | 2019 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/2283 | |
dc.description.abstract | Skin disease is a common issue faced by many in our society. It often decreases the quality of life and may lead to a disability. Recent AI advancements offers to help people with poor access to skin disease specialists, by identifying skin diseases. An artificially intelligent skin disease identifier will provide the opportunity of an early treatment and a timely recovery to people lacking access to skin disease specialists. AI techniques, including image processing and machine learning, have been explored by researchers in recent decades to intelligently identify skin diseases. This paper presents an in-depth review of the image processing and machine learning techniques used thus far. The aim of this review is to facilitate better and improved approaches. | |
dc.language.iso | en | en_US |
dc.subject | Image Processing | en_US |
dc.subject | Machine Learning | en_US |
dc.subject | Skin Diseases | en_US |
dc.title | Research Directions for Skin Disease Identification Using Image Processing and Machine Learning | en_US |
dc.type | Article Full Text | en_US |
dc.identifier.journal | KDUIRC-2019 | en_US |
dc.identifier.pgnos | 417-423 | en_US |
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