This repository contains the implementation of a Convolutional Neural Network (CNN) for classifying chest X-ray images into three categories: COVID-19, viral pneumonia, and healthy person. The CNN model is developed using TensorFlow and Keras, and it achieves exceptional accuracy in classifying chest X-ray images.
The classification of chest X-ray images is crucial in diagnosing respiratory diseases, especially during pandemics like COVID-19. This project focuses on developing a reliable CNN model capable of accurately categorizing chest X-ray images into relevant classes. By leveraging deep learning techniques, we aim to improve the accuracy and robustness of the classification process.
The CNN model achieved an impressive accuracy of 96.96% on the test set, outperforming traditional machine learning methods. Through systematic experimentation, we identified key factors affecting model performance and emphasized the effectiveness of CNN models in classifying chest X-ray images.
This project is licensed under the MIT License - see the LICENSE file for details.