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ISSN 2063-5346
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A Deep Transfer Learning-Based Approach to Detect Skin Disease

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Md Shariar Kabir, Md. Ahasanul Kobir Opy, Md Sefatullah, Md Parvez Mosaraf, Jakia Khanom, Kazi Shiam Hossain
» doi: 10.31838/ecb/2023.12.si6.647

Abstract

Human body can have many types of disease. Some of those is internal & some of those is external. Here, we talk about external disease. Which is generally attacks the skin. Then it is called skin disease. According to who the skin disease rate in Bangladesh reached 1131 or 16% [1]. It is usually caused by seasonal changes, pollution, dirty environment, allergy and lack of skin care. Other diseases can also be caused for this disease. Our research is about all kinds of skin diseases. First, we have collected images of various skin diseases. Then we classified it using transfer learning-based algorithm. Transfer learning is currently a very popular system that is now used in almost every automation technology in the world. Our main objective is to make people aware of their skin diseases very easily. We have used some transfer learning-based algorithm to classify the skin disease. Some algorithm showed us a very good performance. But among all we have adopt MobileNetV2 and its performance. Which is 99%. We have planned to make an android app by using our adopt model where anyone can check their skin disease & confirm about their disease classification

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