- 期刊
An Intelligent Approach for COVID-19 Detection Using Deep Transfer Learning Model
摘要
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 pa- per, 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% ac- curacy outperforming all compared methods.
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