اكتشاب مرض كوفيد-19 في صور الاشعة باستخدام الشبكات العصبية pdf
ملخص الدراسة:
Based on the best published research from Stanford University, the CheXNet algorithm was developed to diagnose and detect pneumonia from chest X-rays. To achieve better performance than experienced radiologists from the same university, simple changes were made to the algorithm to diagnose 14 pathological condition in the chest X-ray with a performance that exceeds all Previously developed deep learning [1]. In this paper, we experimented with applying a convolutional neural networks (CNN) algorithm in a similar way to the mechanism of work in CheXNet algorithm by using a dataset of 550 Chest X-ray images collected from Kaggle website, some of them are infected with Covid-19 virus. We had an acceptable prediction accuracy of 89.7% which is closed to the results of CheXNet algorithm.
توثيق المرجعي (APA)
خصائص الدراسة
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المؤلف
Musleh, Areej A.wahab Ahmed
Maghari, Ashraf Yunis
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سنة النشر
2020-12
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الناشر:
Institute of Electrical and Electronics Engineers (IEEE)
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المصدر:
المستودع الرقمي للجامعة الإسلامية بغزة
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نوع المحتوى:
Conference Paper
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اللغة:
English
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محكمة:
نعم
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الدولة:
فلسطين
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النص:
دراسة كاملة
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نوع الملف:
pdf