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Automatic detection lung infected COVID-19 disease using deep learning (Convolutional Neural Network) | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، شماره 2، بهمن 2021، صفحه 921-929 اصل مقاله (582.24 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5148 | ||
| نویسندگان | ||
| Mali H. Hakem Alameady* 1؛ Ahmed Fahad2؛ Alaa Abdullah3 | ||
| 1Department of Computer Science, Faculty of Computer Science and Maths, University of Kufa, Najaf, Iraq | ||
| 2University of Thi-Qar, 64001 Al-Nassiriya, Iraq | ||
| 3Education Directorate of Thi-Qar, Ministry of Education, Iraq | ||
| تاریخ دریافت: 21 فروردین 1400، تاریخ بازنگری: 23 اردیبهشت 1400، تاریخ پذیرش: 05 خرداد 1400 | ||
| چکیده | ||
| 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%. | ||
| کلیدواژهها | ||
| Deep learning؛ Convolutional Neural Network؛ COVID-19 | ||
| مراجع | ||
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