Skin Disease Detection Using Convolutional Neural Network and Support Vector Machine Classification

Abstract

Dermatological issues are one of the most preventable diseases in the world. Diagnosing skin problems early is essential for effective therapy. The method for identifying and treating skin injury is based on the specialist’s level of competence and experience. Skin disease diagnosis has benefited from the application of AI calculations and the utilization of the large quantity of information available in hospitals and clinics. Existing the specialists employed numerous frameworks, instruments, and calculations. A small number of frameworks have been developed that are capable of correctly identifying skin diseases with varying degrees of suggestive precision. In this proposed convolutional neural networks and Support Vector Machine are used this approach is simple, fast and does not require expensive equipment other than a camera and a computer. The process makes use of machine learning technology to train itself with the various skin images. The main objective of this process is to increase the accuracy of skin disease detection and the three important features in image classification are texture, color and shape.