Chest X-Ray Images Classification
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Deep Learning
Transfer Learning
Data Enhancement
Date
Summary
Summary: Use three different deep convolutional neural network models to deal with the classification of Chest
X-image classification for biomedical treatment. The Chest X-image dataset are divided into Bacterial pneumonia, Virus pneumonia, COVID-19 and several other categories. Applied data augmentation, data enhancement and transfer learning methods to the training dataset during the multiple classification problem. The final accuracy of the InceptionResNetV2 achieve an accuracy of 100% in binary classification problem and an accuracy of 97.45% in multiple classification problem.