SKIN DISEASES RECOGNITION USING CNN ALGORITHM

Abstract

The human skin is an extraordinary structure that frequently encounters both known and unknown diseases. Conducting regular and thorough skin examinations plays a vital role in the early detection of any detrimental or incipient changes in the skin, which could potentially lead to skin disease. This research paper is dedicated to addressing this challenge by proposing an effective solution using ML models, specifically a Convolutional Neural Network (CNN) system. The proposed CNN model exhibits superior accuracy in recognizing different types of skin diseases. By harnessing the power of machine learning techniques, it contributes to the development of robust systems capable of detecting various classes of skin ailments. In this paper, the CNN machine learning algorithm is chosen and implemented on a dataset of skin infection cases to accurately predict the specific class of skin disease. Among the numerous machine learning algorithms explored, CNN stands out as the optimal choice for effectively detecting skin diseases, providing precise disease identification, and reporting the corresponding accuracy levels.