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    An Optimized CNN Model Architecture for Detecting Coronavirus (COVID-19) with X-Ray Images

    Anas Basalamah1, Shadikur Rahman2,*

    Computer Systems Science and Engineering, Vol.40, No.1, pp. 375-388, 2022, DOI:10.32604/csse.2022.016949

    Abstract This paper demonstrates empirical research on using convolutional neural networks (CNN) of deep learning techniques to classify X-rays of COVID-19 patients versus normal patients by feature extraction. Feature extraction is one of the most significant phases for classifying medical X-rays radiography that requires inclusive domain knowledge. In this study, CNN architectures such as VGG-16, VGG-19, RestNet50, RestNet18 are compared, and an optimized model for feature extraction in X-ray images from various domains involving several classes is proposed. An X-ray radiography classifier with TensorFlow GPU is created executing CNN architectures and our proposed optimized model for More >

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