Detection and Recognition of COVID-19 CT Images - Sallomi, Adheed; Al-Delfi, Hussein (Journal of Madenat Alelem University College, 2023)
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%.