Comparison of deep learning models based on chest x-ray image classification

HIGHLIGHTS

• What: Through this study the authors showcase the potential application of image methods in pneumonia detection and provide performance comparisons among different models. This study provides a foundation for further improvements and optimizations in lung infection detection technology, thereby enhancing the efficiency and accuracy of medical diagnosis and monitoring. This model has a large number of parameters, reaching 53,155,512, requiring further model compression . The authors utilized InceptionV3, VGG16, MobileNetV2 as the base models to evaluate their performance on the classification task using the Chest X-Ray Images (Pneumonia) dataset.
• Who: Chest X-Ray . . .
  

   

  

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