A modified CNN-based Covid-19 detection using CXR
<p>In this paper, a deep neural network for the purpose of detecting COVID-19 from Chest X-Ray (CXR) images is presented. Since this pandemic has emerged worldwide , there is no large dataset available for it. So for its detection, care must be taken not to use methods with high variance. Howe...
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| Main Authors: | , , |
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| Format: | Book |
| Published: |
Archives of Community Medicine and Public Health - Peertechz Publications,
2021-07-24.
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| Online Access: | Connect to this object online. |
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| Summary: | <p>In this paper, a deep neural network for the purpose of detecting COVID-19 from Chest X-Ray (CXR) images is presented. Since this pandemic has emerged worldwide , there is no large dataset available for it. So for its detection, care must be taken not to use methods with high variance. However, for a deep neural network to get acceptable performance, we usually need huge amounts of datasets. Otherwise, there may be issues like overfitting. To resolve this problem, we use the beautiful idea of transfer learning. Training a deep neural network with the idea of transfer learning on 2 available datasets on the web, we achieved a COVID-19 detection accuracy of 98% on about 1000 test samples.</p><p>1(Use footnote for providing further information about author (webpage, alternative address)-not for acknowledging funding agencies.)</p> |
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| DOI: | 10.17352/2455-5479.000154 |