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Classification of Pneumonia on Chest X-Ray Image Using Transfer Learning

EasyChair Preprint no. 10369

8 pagesDate: June 9, 2023


Pneumonia is a dangerous disease and often causes death if not detected and treated promptly. According to the World Health Organization (WHO), every year about 3 million people die from pneumonia worldwide. In this study, we will focus on classifying pneumonia based on traditional machine learning techniques Convolutional Neural Networks (CNNs) with model ResNet50 for the problem of classifying pneumonia through the classification of X-ray images into 3 classes Normal, Bacterial, Viral. We collect X-ray image data from a variety of data sources to build a large and diverse dataset. Evaluation results on a dataset of 2500 X-ray images of the lungs with 710 Normal images, 1080 Bacterial images, 710 Viral images, training and experimental results are the basis for further studies.

Keyphrases: Classification of pneumonia, ResNet50, X-rays images

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Thi Bích Nhu Pham and Minh Hong Nguyen},
  title = {Classification of Pneumonia on Chest X-Ray Image Using Transfer Learning},
  howpublished = {EasyChair Preprint no. 10369},

  year = {EasyChair, 2023}}
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