Highly Robust and Efficient Random Feature Coordination Schema using DNN for Melanoma Skin Cancer Detection

Abstract

Melanoma skin cancer is transferable and spread from one origin to another and hence considered as most fatal cancer type in the world by WHO. Researchers have proposed various auto diagnostic techniques and instrumentations for progressive detection and classification of melanoma cancer. In the research article, a novel approach of random feature coordination schema is proposed to identify and categorize skin cancer. The technique includes a deep neural networking (DNN) framework to categorize and provide reliable decision support on processing data-types. The technique has demonstrated 93.48% accuracy in customizing the datasets and providing decision support.

Topics & Concepts