School of Computer Engineering (November 2021)

2,022

Book Chapter

1. Purohit, S., Suman, S., Kumar, A., Sarkar, S. Pradhan, C., and Chatterjee J. (2021), Comparative Analysis for Detecting Skin Cancer Using SGD-based Optimizer on a CNN versus DCNN Architecture and ResNet-50 versus AlexNet on Adam Optimizer in Deep Learning for Personalized Healthcare Services, Vishal Jain, Jyotir Moy Chatterjee, Hadi Hedayati (Eds.), De Gruyter,  pp. 185–203.

Abstract

This work presents a deep learning technique to classify images and detect skin cancer at an early stage. We have trained our model using images of harmless, that is benign, images and tumor-based images; we have used convolutional neural network on those images to classify whether the image is a suspect of skin cancer or not. This proposed approach achieved an accuracy of 86% and is compared to the DCNN model. Also, an additional approach using the ResNet-50, a 50-layer deep CNN has been implemented which has proved useful in further improving the accuracy to over 90%.



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