A Transfer Learning-Based Approach with Deep CNN for COVID-19- and Pneumonia-Affected Chest X-ray Image Classification.
Chakraborty S, Paul S, Hasan KMA.
SN computer science. 2022; 3(1): 17

Abstract

The COVID-19 pandemic creates a significant impact on everyone's life. One of the fundamental movements to cope with this challenge is identifying the COVID-19-affected patients as early as possible. In this paper, we classified COVID-19, Pneumonia, and Healthy cases from the chest X-ray images by applying the transfer learning approach on the pre-trained VGG-19 architecture. We use MongoDB as a database to store the original image and corresponding category. The analysis is performed on a public dataset of 3797 X-ray images, among them COVID-19 affected (1184 images), Pneumonia affected (1294 images), and Healthy (1319 images) (https://www.kaggle.com/tawsifurrahman/covid19-radiography-database/version/3). This research gained an accuracy of 97.11%, average precision of 97%, and average Recall of 97% on the test dataset. CI - (c) The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2021.



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