Derma Net: An Automated Skin Lesion Analyzer using CNN with Adaptive Learning

• Published in: International journal of innovative technology and exploring engineering Vol. 8; no. 6S4; pp. 513 - 515
• Format: Journal Article
• Language: English
• Published: 26.07.2019
• ISSN: 2278-3075; 2278-3075
• DOI: 10.35940/ijitee.F1107.0486S419

In this paper we are going to develop an automated skin lesion analyzer that can take affected skin lesion image from user and predict or approximate 3 skin diseases with 95% accuracy. To accomplish this goal we are going to use Neural Networks as they are the best data driven models with top most accuracy in all the fields they have been experimented till now. Since Neural Network models also need huge computation power to train the model on the input data and also to predict the output we are going to use a computationally less intensive architecture that can work even on hand held mobiles and embedded systems. To further featuring our model we have added dropout techniques for model regularization and adaptive learning rates to achieve global minima with ease even with the presence of plateaus. At last we will deploy a production level web application to serve users across the world