Detection and Recognition of COVID-19 CT Images

Authors

  • 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%.

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Published

2023-12-19

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Section

Articles

How to Cite

[1]
“Detection and Recognition of COVID-19 CT Images”, JMAU, vol. 15, no. 2, pp. 1–7, Dec. 2023, Accessed: Feb. 17, 2026. [Online]. Available: https://journal.mauc.edu.iq/index.php/JMAUC/article/view/492