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DCNN for COVID-19 X-Ray Classification by apatz is a document available to read on EtoBox.
What is DCNN for COVID-19 X-Ray Classification about?
The paper presents a Deep Convolutional Neural Network (DCNN) for classifying COVID-19, pneumonia, and normal patients using chest X-ray images, achieving a test accuracy of 94.95%. It integrates an IoT framework for efficient communication between users and the model, addressing challenges in COVID-19 diagnosis due to the similarities in radiological features of pneumonia. The study emphasizes the need for effective diagnostic tools in the ongoing pandemic and utilizes datasets from Kaggle and GitHub for t
- Author
- apatz
- Language
- EN