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ResNet based Deep Learning model for Skin Diseases Classification

Dr. M. Umamaheswari, Yogananda Arisetty, Shobhana Joshi, Pavani Bajjuri

International Journal of Advanced Research in Science, Communication and Technology(2022)

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摘要
Skin disease are commonest than other diseases. It might be caused by bacteria, parasites and viruses etc. The Advanced medical technology has made it possible to identify the skin disease faster and accurate. However, the cost of such skin diseases remains limited and expensive. So image processing techniques aid in the development of an automated screening system for dermatology at an early stage. The features extraction plays vital role in the classification of skin diseases. Computer vision has a function in the detection of pores and skin illnesses in variety of strategies. This research aims to detect three common diseases such as acne, hyper pigmentation and psoriasis. We proposed an image processing techniques that accepts the digital image of disease, then image analysis to identify the type of disease. The proposed method is very simple, fast and does not need any additional equipment. It accepts input of color image and it resizes the image to extract features using CNN. Then multi class features are classified using first order feature extraction method. Lastly, the type of disease, spread and severity are shown to the user. The system identifies three different types of disease accurately.
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关键词
deep learning model,deep learning,skin,classification,diseases
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