Ensemble of Patches for COVID-19 X-Ray Image Classification

Thiago Dong Chen; Gabriel Bianchin de Oliveira; Zanoni Dias

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Paper

Ensemble of Patches for COVID-19 X-Ray Image Classification

Topics: Deep Learning; Machine Learning; Neural Networks

In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, 561-567, 2022

Authors: Thiago Dong Chen ; Gabriel Bianchin de Oliveira and Zanoni Dias

Affiliation: Institute of Computing, University of Campinas, Campinas, SP, Brazil

Keyword(s): COVID-19, Deep Learning, X-Ray Images Classification.

Abstract: With the COVID-19 pandemic, several efforts have been made to develop quick and effective diagnoses to assist health professionals in decision-making. In this work, we employed convolutional neural networks to classify chest radiographic images of patients between normal, pneumonia, and COVID-19. We evaluated the division of the images into patches, followed by the ensemble between the specialist networks in each of the image’s parts. As a result, our classifier reached 90.67% in the test, surpassing another method in the literature.

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Paper citation in several formats:

Chen, T. ; Oliveira, G. and Dias, Z. (2022). Ensemble of Patches for COVID-19 X-Ray Image Classification. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-547-0; ISSN 2184-433X, SciTePress, pages 561-567. DOI: 10.5220/0010864500003116

@conference{icaart22,
author={Thiago Dong Chen and Gabriel Bianchin de Oliveira and Zanoni Dias},
title={Ensemble of Patches for COVID-19 X-Ray Image Classification},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2022},
pages={561-567},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010864500003116},
isbn={978-989-758-547-0},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Ensemble of Patches for COVID-19 X-Ray Image Classification
SN - 978-989-758-547-0
IS - 2184-433X
AU - Chen, T.
AU - Oliveira, G.
AU - Dias, Z.
PY - 2022
SP - 561
EP - 567
DO - 10.5220/0010864500003116
PB - SciTePress