X-Ray Image Classification for COVID-19 Using Transfer Learning

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Abstract

SARS-CoV-2, the cause of one of the significant pandemics in history, first appeared in Wuhan, China. It spreads rapidly, with symptoms like fever, cough, tiredness, and loss of taste or smell. We came up with many measures where the most effective was vaccines. Yet it's not enough against the rapidly appearing waves of SARS-CoV-2. A deep learning algorithm has proven efficient in detecting Covid-19 based on pneumonia and respiratory problems. These problems have been identified with the help of CT scans and X-ray images. It'll make it a lot easier to determine who's Infected and would save a lot of time and expenses overall would provide for extensive relief in the Covid-19 pandemic. This paper uses publically available COVID-19 X-Ray and CT Scan images to create a dataset. The Deep Learning based model is used to train and test the dataset. In the experiment, the overall accuracy is 98%, and in the testing process, the overall accuracy is 99%.

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APA

Abhishek, Ranjan, R., & Sahni, R. (2023). X-Ray Image Classification for COVID-19 Using Transfer Learning. In Advances in Transdisciplinary Engineering (Vol. 32, pp. 522–528). IOS Press BV. https://doi.org/10.3233/ATDE221307

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