Variability Evaluation of CNNs using Cross-validation on Viruses Images
André R. Backes, André R. Backes, Jefferson R. Souza
2020
Abstract
Virus description and recognition is an essential issue in medicine. It helps researchers to study virus attributes such as its morphology, chemical compositions, and modes of replication. Although it can be performed through visual inspection, it is a task highly dependent on a qualified expert. Therefore, the automation of this task has received great attention over the past few years. In this study, we applied transfer learning from pre-trained deep neural networks for virus species classification. Given that many image datasets do not specify a fixed training and test sets, and to avoid any bias, we evaluated the impact of a cross-validation scheme on the classification accuracy. The experimental results achieved up to 89% of classification accuracy, outperforming previous studies by 2.8% of accuracy.
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in Harvard Style
R. de Geus A., Backes A. and Souza J. (2020). Variability Evaluation of CNNs using Cross-validation on Viruses Images. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 626-632. DOI: 10.5220/0009352106260632
in Bibtex Style
@conference{visapp20,
author={André R. R. de Geus and André R. Backes and Jefferson R. Souza},
title={Variability Evaluation of CNNs using Cross-validation on Viruses Images},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP},
year={2020},
pages={626-632},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009352106260632},
isbn={978-989-758-402-2},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 4: VISAPP
TI - Variability Evaluation of CNNs using Cross-validation on Viruses Images
SN - 978-989-758-402-2
AU - R. de Geus A.
AU - Backes A.
AU - Souza J.
PY - 2020
SP - 626
EP - 632
DO - 10.5220/0009352106260632
PB - SciTePress