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Deep Convolutional Neural Network Models using Deep Transfer Learning through the Xception Architecture for computer-aided chest xray diagnosis

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X-COVNets

This repository aims to provide a library of open-source models for computer-aided diagnosis of pneumonia-like lung diseases. Using deep transfer learning through the Xception architecture, Deep Convolutional Neural Network Models have been trained on the COVID-19 Chest X-Ray Database to classify COVID-19, pneumonia, and healthy patients.

X-CovNet Specifications

  • Image Scale: 0-1

  • Image Size: 224x224x3

  • Class Mode: Categorical

  • Interpolation: Bicubic

  • External Validation: ✅

Collaborating Universities and Research Centers

  • University of Computer Sciences, Havana, Cuba (UCI)
  • Center for Medical Informatics (CESIM)
  • Center for Computational Mathematics Studies (CEMC).

Authors

  • Jorge Félix Martínez Pazos
  • Arturo Orellana García
  • Jorge Gulín Gonzáles
  • David Batard Lorenzo

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Deep Convolutional Neural Network Models using Deep Transfer Learning through the Xception Architecture for computer-aided chest xray diagnosis

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