Opis

• Tytuł:
  Neural networks for the Recognition of X-ray Images of Ailments for Covid-19
• Twórca:
  Diachenko, Liliia;
  Lazoriak, Oleksandr;
  Dobrovolsky, Yurii;
  Prokhorov, Georgii;
  Shumyliak, Liliia
• Opis:
  This investigation analyzes the current state of neural networks, considers the available types, optimizers used for training, describes their benefits and disadvantages. The task of computer vision is defined and the answer to the question why the use of neural networks is an important task today is given. The powerful neural network from Google was proposed as an example and its algorithm is described in detail. Studies have shown how to configure models to get high performance.
• Dostępność obiektu:
  Dostęp otwarty
• Prawa:
  Prawa autorskie (c) 2022 Liliia Diachenko, Oleksandr Lazoriak, Yurii Dobrovolsky, Georgii Prokhorov, Liliia Shumyliak;
  http://creativecommons.org/licenses/by-nc-sa/4.0
• Data:
  2022.04.26
• Typ:
  info:eu-repo/semantics/article;
  info:eu-repo/semantics/publishedVersion
• Język:
  angielski
• Źródło:
  Journal of Education, Health and Sport; Vol. 12 No. 6 (2022); 26-38;
  Journal of Education, Health and Sport; Tom 12 Nr 6 (2022); 26-38;
  2391-8306
• Format:
  application/pdf
• Wydawca:
  Nicolaus Copernicus University, Toruń, Poland
• Relacja: https://apcz.umk.pl/JEHS/article/view/38107/32070
• Temat i słowa kluczowe:
  Convolutional neural network;
  computer vision;
  optimizers;
  X-rays;
  model;
  Covid-19;
  machine learning
• Identyfikator: https://apcz.umk.pl/JEHS/article/view/38107
• Dostawca danych:
  Akademicka Platforma Czasopism
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