Deep Learning Models of Melonoma Image Texture Pattern Recognition

Abstract

Melanoma is treated as one of the most hazardous skin disease, which must be identified in earlier for a proper treatment and diagnosing. The Computer Aided Diagnosis (CAD) system is more helpful to exactly detect and classify the disease based on its features. This paper aims to conduct a detailed review on different types of image processing techniques used for detecting the skin disease with improved efficiency and accuracy measures. There are several models of image feature analysis and prediction methods based on the neural network to enhance the classification rate. In this paper, the techniques related to the neural network based classification models are analyzed and reviewed with its benefits and demerits. Also, this work aims to investigate the performance of each technique based on several evaluation measures. Based on this study, the most suitable technique is identified for the Melanoma skin disease detection with high detection efficiency.