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The proposed model provides a multi-class classification of lung X-ray images into COVID-19, non-COVID Pneumonia, and normal (healthy). The proposed systems' performance is assessed based on the evaluation metrics such as accuracy, sensitivity, precision, and f1 score. The current research employed a dataset size of 7500 X-ray samples. The high recognition accuracy of 99.67% was observed for the proposed COVID-DeepNet model, and it complies with the most recent state-of-the-art. The proposed COVID-DeepNet model is highly efficient and ac
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