Skin Disease Classification Using Hybrid Approach

Authors : Ashwini Shinde; Madhav Ingle

Volume/Issue : Volume 7 - 2022, Issue 12 - December

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Skin infections are more normal than different illnesses. Skin sicknesses might be brought about by contagious contamination, microorganisms, sensitivity, or infections, and so on. The headway of lasers and photonics based clinical innovation has made it conceivable to analyze the skin infections considerably more rapidly and precisely. However, the expense of such conclusion is as yet restricted and extravagant. Along these lines, picture handling methods help to fabricate robotized evaluating framework for dermatology at an underlying stage. The extraction of elements assumes a vital part in assisting with ordering skin illnesses considerably more rapidly and precisely. PC vision plays a vital part in the discovery of skin illnesses in different procedures. This paper concentrates on four skin sicknesses Ringworm, Nail Parasite, Psoriasis, Atopic dermatitis. Then again, the Convolutional Neural Network have accomplished close or far better execution than people in the imaging field. We are classifying the disease through machine learning algorithm i.e. random forest

Keywords : Skin Disease Detection, Convolutional Neural Network, Image Processing, Deep Learning, Machine Learning, Random Forest.


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31 - March - 2023

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