COMPARISON OF DEEP NEURAL NETWORKS BASED ON DIFFERENT PRE-TRAINED CNN FOR COVID-19 DIAGNOSIS FROM X-RAY IMAGES

Authors

  • Verzunov S.N. Machinery researching Institute of the National Academy of Sciences of the Kyrgyz Republic
  • Raimzhanov Kh.A. Kyrgyz-Russian Slavic University

Keywords:

COVID-19, deep learning, CNN, pretrained convolutional networks.

Abstract

Clinical studies have found that chest x-rays can be of great value in diagnosing patients with COVID-19, especially in addressing the lack of capacity in ambulances and hospitals. Deep learning methods are currently playing a dominant role in the development of high-performance classifiers for chest X-ray detection of this disease.

Given that many new neural network models have been developed for this purpose, the aim of this study is to explore options for trained convolutional neural networks to diagnose COVID-19 using chest x-rays.

 

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Published

2021-05-03

How to Cite

Verzunov, S. N., & Raimzhanov, H. A. (2021). COMPARISON OF DEEP NEURAL NETWORKS BASED ON DIFFERENT PRE-TRAINED CNN FOR COVID-19 DIAGNOSIS FROM X-RAY IMAGES. Problemy Avtomatiki I Upravleniâ, (1), 12–25. Retrieved from https://pau.imash.kg/index.php/pau/article/view/187

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Section

INFORMATION TECHNOLOGY AND INFORMATION PROCESSING

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