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automatic detection lung infected covid-19 disease using deep learning (convolutional neural network)
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نویسنده
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alameady mali h. hakem ,fahad ahmed ,abdullah alaa
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منبع
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international journal of nonlinear analysis and applications - 2021 - دوره : 12 - شماره : 2 - صفحه:921 -929
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چکیده
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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%.
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کلیدواژه
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deep learning ,convolutional neural network ,covid-19
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آدرس
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university of kufa, faculty of computer science and maths, department of computer science, iraq, university of thi-qar, iraq, ministry of education, education directorate of thi-qar, iraq
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پست الکترونیکی
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anf.alfahad@gmail.com
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Authors
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