Fog Computing for Intelligent Cloud IoT Systems

10Fog Computing-Enabled Cancer Cell Detection System Using Convolution Neural Network in Internet of Medical Things

Soumen Santra¹*, Dipankar Majumdar² and Surajit Mandal³

¹ Department of MCA, Techno International New Town, Kolkata, West Bengal, India

²Department of CSE, RCC Institute of Information Technology, Kolkata, West Bengal, India

³Department of ECE, B.P. Poddar Institute of Management and Technology, Kolkata, West Bengal, India

Abstract

Computer-enabled smart home management systems are very flexible in nature and easy to use as hand-held devices. This type of feature selection device is currently used in health management systems. The health management system is a service or HaaS that provides all kinds of facilities to the patient by which they can understand the status of the disease, just like medical practitioners. Convolutional neural networks (CNNs) are a special subset of deep learning (DL), which is used to fetch hidden features through multiple hidden layers from images and produce optimum output. Because cancerous images contain huge amounts of information, these large-scale datasets require high computational power to process properly and provide proper output within a short span of time. The CNN model is implemented in Google Collaboratory (Colab) where we import a large-scale dataset through a customized model. This model contains a CNN layer, average pool layer, and MaxPool layer through which we pass the image dataset. The Deep CNN (DCNN) fetches mostly ...