COVID-19 Detection based on Lung CT Images using Convolutional Neural Network Architecture

Abstract

Abstract: A CNN (Convolutional Neural Network) is a class of deep neural networks that are most used for analyzing visual imagery. This is the most widely used deep learning algorithm for image and video recognition, image classification, image segmentation, medical image analysis and natural language processing, and many more. But, training the Neural Network from scratch requires more training time and requires a lot of data, and the performance of the model is affected. ‘Transfer learning’ is the best approach where existing architectures that have been trained on the large datasets are then fine-tuned for our customized dataset. This reduces the time to train and often results in better performance.

The main objective of this paper is to detect COVID-19 from lung CT images using the VGG16 CNN (Convolutional Neural Network) model from the ImageNet.

Index Terms: CNN, Transfer learning, VGG16, and ImageNet.