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Skin Disease Recognition

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dc.contributor.author Nawar, Anika
dc.contributor.author Sabuz, Noor Kibria
dc.contributor.author Siddiquee, Shah Md. Tanvir
dc.contributor.author Rabbani, Masud
dc.contributor.author Biswas, Al Amin
dc.contributor.author Majumder, Anup
dc.date.accessioned 2022-04-16T09:23:02Z
dc.date.available 2022-04-16T09:23:02Z
dc.date.issued 2021-06-03
dc.identifier.uri http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7856
dc.description.abstract Progressively a large number of people are being invaded by various types of skin diseases all over the world. With the help of modern medical equipment, it is very much easy to find out the diseases. But sometimes people wouldn't able to reach a hospital or any diagnostic center in a short time and it is also very much costly for most people especially for developing country. In that scenario, we proposed a prototype in this paper by which we can recognize the problem urgently and at a low cost. Mainly this is an image processing technique. Using color segmentation technique with SVM classifier, our proposed system can recognize several types of skin diseases based on some feature extraction. This method efficiently recognizes eight different skin diseases with an accuracy rate of percentage is 94.79%. Our recommended model is so simple, fast, and requires any kinds of programmable devices like desktop, android phones, tabs, IOS, and so on. en_US
dc.language.iso en_US en_US
dc.publisher 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), IEEE en_US
dc.subject Machine vision en_US
dc.subject Performance metric en_US
dc.subject Recognition en_US
dc.subject SVM en_US
dc.subject Skin diseases en_US
dc.subject Classification en_US
dc.title Skin Disease Recognition en_US
dc.title.alternative a Machine Vision Based Approach en_US
dc.type Article en_US


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