Skin Disease Detection and Recommendation System using Deep Learning and Cloud Computing

Abstract

The main objective of this research is to develop an application based on Deep learning, Computer vision and cloud computing that detects the different kinds of skin diseases caused by different types of viruses, Bacteria, Fungus and Environment. This study has also developed and integrated a recommendation system, which recommends the medicines and care taking process for a particular disease. The application also suggests preventive methods for different kinds of skin infections. This study used an ensemble of convolution neural networks (CNN) with generative adversarial network (GAN) and Computer vision for construction of the model. Further, Amazon Personalize is used to build recommendation system in the proposed web application. The proposed application detects the disease based on symptoms, pictures, and videos of infected skin area. The application will be helpful for dermatologists and common people to perform early detection and prevention of skin diseases in India. This study also compared the accuracy of ensemble of convolution neural networks (CNN) with GAN and other algorithms like CNN. In comparison of accuracy, this study found that the Ensembles of CNN with GAN give best results for the proposed dataset.