Impact of Chest X-ray Images Enhancement to COVID-19 Classification Using Vector Quantization and Fuzzy S-tree
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-14627-5_38
Reference24 articles.
1. Chen, N., et al.: Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The lancet 395(10223), 507–513 (2020)
2. Chowdhury, M.E.H., et al.: Can AI help in screening viral and COVID-19 pneumonia? IEEE Access 8, 132665–132676 (2020)
3. Rahman, T., et al.: Exploring the effect of image enhancement techniques on COVID-19 detection using chest x-ray images. Comput. Biol. Med. 132, 104319 (2021)
4. Alyasseri, Z.A.A., et al.: Review on COVID-19 diagnosis models based on machine learning and deep learning approaches. Expert Syst. 39(3), e12759 (2022)
5. Wang, L., Lin, Z.Q., Wong, A.: COVID-Net: a tailored deep convolutional neural network design for detection of COVID-19 cases from chest x-ray images. Sci. Rep. 10(1), 1–12 (2020)
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