Title of article :
Automatic detection lung infected COVID-19 disease using deep learning (Convolutional Neural Network)
Author/Authors :
Hakem Alameady, Mali H. Department of Computer Science - Faculty of Computer Science and Maths - University of Kufa, Najaf, Iraq , Fahad, Ahmed University of Thi-Qar, Al-Nassiriya, Iraq , Abdullah, Alaa Education Directorate of Thi-Qar - Ministry of Education, Iraq
Pages :
9
From page :
921
To page :
929
Abstract :
In late 2019, a virus appeared suddenly he claims Covid-19, which started in China and began to spread very widely around the world. an‎d because of its effects, which are not limited to human life only, but rather in economic and social aspects, and because of the increase in daily injuries and significantly with the limited hospitals that cannot accommodate these large numbers, it is necessary to find an automatic and rapid detection method that limits the spread of the disease and its detection at an early stage in order to be treated more quickly. In this paper, deep learning was relied upon to create a CNN model to detect COVID-19 infected lungs using chest X-ray images. The base consists of a set of images taken of lungs infected with Covid-19 disease and normal lungs, as the CNN structure gave accuracy, Precision, Recall and F-Measure 100%
Keywords :
Deep learning , Convolutional Neural Network , COVID-19
Journal title :
International Journal of Nonlinear Analysis and Applications
Serial Year :
2021
Record number :
2701660
Link To Document :
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