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REFERENCES

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A. S. Al-Waisy, S. Al-Fahdawi, M. A. Mohammed, K. H. Abdulkareem, S. A. Mostafa, M. S. Maashi, M. Arif, and B. Garcia-Zapirain, ``COVID-CheXNet: Hybrid deep learning framework for identifying COVID-19 virus in chest X-rays images,'' Soft Computing, vol. 27, no. 5, pp. 2657-2672, 2023.DOI
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H. Kibriya and R. Amin, ``A residual network-based framework for COVID-19 detection from CXR images,'' Neural Computing and Applications, vol. 35, no. 11, pp. 8505-8516, 2023.DOI
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F. Mercaldo, M. P. Belfiore, A. Reginelli, L. Brunese, and A. Santone, ``Coronavirus covid-19 detection by means of explainable deep learning,'' Scientific Reports, vol. 13, no. 1, 2023.DOI
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A. S. Al-Waisy, S. Al-Fahdawi, M. A. Mohammed, K. H. Abdulkareem, S. A. Mostafa, M. S. Maashi, M. Arif, and B. Garcia-Zapirain, ``COVID-CheXNet: Hybrid deep learning framework for identifying COVID-19 virus in chest X-rays images,'' Soft Computing, vol. 27, no. 5, pp. 2657-2672, 2023.DOI
19 
H. Mzoughi, I. Njeh, M. B. Slima, and A. B. Hamida, ``Deep efficient-nets with transfer learning assisted detection of COVID-19 using chest X-ray radiology imaging,'' Multimedia Tools and Applications, pp. 1-23, 2023.DOI
20 
P. Sharma, R. Arya, R. Verma, and B. Verma, ``Conv-CapsNet: Capsule-based network for COVID-19 detection through X-ray scans,'' Multimedia Tools and Applications, pp. 1-25, 2023.DOI
21 
Z. Ullah, M. Usman, S. Latif, and J. Gwak, ``Densely attention mechanism based network for COVID-19 detection in chest X-rays,'' Scientific Reports, vol. 13, no. 1, 261, 2023.DOI
22 
A. Narula and N. K. Vaegae, ``Development of CNN-LSTM combinational architecture for COVID-19 detection,'' Journal of Ambient Intelligence and Humanized Computing, vol. 14, no. 3, pp. 2645-2656, 2023.DOI