Detection and Recognition of COVID-19 CT Images

  • Adheed H. Sallomi
  • Hussein A. Hussein Al-Delfi

Abstract

Most of the world's countries have seen the 2019 coronavirus disease (COVID-19) spread quickly. The globe has been dealing with a global health crisis since 2019. To combat COVID-19, automated identification of lung infections is essential. It is known that the most recent coronavirus originated in the Chinese city of Wuhan. It is a novel coronavirus that poses a risk to humans and was identified for the first time in December 2019, according to the World Health Organization (WHO). The bi-branch feature fusion network topology suggested by this study is built on Transformer modules and Convolutional Neural Network modules. When using CT scans for COVID-19 classification, it performs well; the classification accuracy is 97%.

Published
2023-12-19
How to Cite
[1]
A. Sallomi and H. Al-Delfi, “Detection and Recognition of COVID-19 CT Images”, JMAUC, vol. 15, no. 2, pp. 1-7, Dec. 2023.
Section
Articles