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publication name An Intelligent Approach for COVID-19 Detection Using Deep Transfer Learning Model
Authors Mustafa Abdul Salam, Mohamed A Torad
year 2021
keywords
journal
volume Not Available
issue Not Available
pages Not Available
publisher Not Available
Local/International International
Paper Link http://ijeie.jalaxy.com.tw/contents/ijeie-v13-n2/ijeie-2021-v13-n2-p66-76.pdf
Full paper download
Supplementary materials Not Available
Abstract

Coronavirus disease (COVID-19) appeared in the last quarter of 2019. A Coronavirus wildfire around the world, where the infection and death rates uprise dramatically every day. In this paper, an enhanced convolutional neural network based on transfer learning was proposed to detect patients infected with COVID-19 using chest X-ray radiographs. The proposed model helps radiologists to diagnose COVID-19 disease automatically with high accuracy. The proposed method is introduced to afford precise identification of infected persons. Referring to the performance results acquired, the used pre-trained ResNet50 paradigm achieves the peak performance with 99.2% accuracy outperforming all compared methods.

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