Abstract
Viruses and bacteria are now much more dangerous than ever because of their ability to develop their immune systems against medicines. COVID-19 spread rapidly over the entire world. Intelligent systems are needed to help doctors determine whether there is an infection or not. Convolution Neural Network is a class of deep learning which can analyze visual images. This paper investigates Convolution Neural Network CNN’s effectiveness in recognizing the infected lung images with COVID-19 or any other diseases. The proposed CNN model classifies the lung X-ray into three categories COVID-19, pneumonia, and normal. The model was applied using Cohen and collected databases from Kaggle and GitHub. The proposed model achieved an average accuracy of 96.8% to classify between COVID-19, pneumonia, and normal lungs x-rays, and 100% accuracy to classify COVID-19 versus normal lungs X-rays images.
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Ghaleb, M.S., Ebied, H.M., Shedeed, H.A., Tolba, M.F. (2021). COVID-19 X-rays Model Detection Using Convolution Neural Network. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_1
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