این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
International Journal of Nonlinear Analysis and Applications، جلد ۱۲، شماره ۲، صفحات ۹۲۱-۹۲۹
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی Automatic detection lung infected COVID-19 disease using deep learning (Convolutional Neural Network)
چکیده انگلیسی مقاله 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%
کلیدواژه‌های انگلیسی مقاله Deep learning, Convolutional Neural Network, COVID-19
نویسندگان مقاله Mali H. Hakem Alameady |
Department of Computer Science, Faculty of Computer Science and Maths, University of Kufa, Najaf, Iraq

Ahmed Fahad |
University of Thi-Qar, 64001 Al-Nassiriya, Iraq

Alaa Abdullah |
Education Directorate of Thi-Qar, Ministry of Education, Iraq

نشانی اینترنتی https://ijnaa.semnan.ac.ir/article_5148_9cb33dcb6e8850fb48ae898898cc890c.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات