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Authors: Cristopher Morales ; Edgar Cavero and Willy Ugarte

Affiliation: Department of Computer Science, Universidad Peruana de Ciencias Aplicadas, Lima, Peru

Keyword(s): YoloV5, Computer Vision, Blueberry, Machine Learning, Plague, Disease.

Abstract: The following research presents a mobile application that can recognize the following plages usually found on blueberry leaves: oidium, heliothis and alternaria. These diseases affects the growth of the bush an thus reduce its yield. Additionally, an open dataset will be available for future investigations. Yolov5, a convolutional neural network, is used for the development of the model, data collection was performed in the Fundo San Roberto, Huaral-Peru, and data augmentation techniques were used to increment the amount of workable data. Thanks to this the following results were obtained: accuracy of 84% and recall of 91%. We predict that the model could be improved to recognize other plages given the right amount of data.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Morales, C.; Cavero, E. and Ugarte, W. (2023). DrBerry: Detection of Diseases in Blueberry Bush Leaves. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR; ISBN 978-989-758-671-2; ISSN 2184-3228, SciTePress, pages 355-364. DOI: 10.5220/0012207100003598

@conference{kdir23,
author={Cristopher Morales. and Edgar Cavero. and Willy Ugarte.},
title={DrBerry: Detection of Diseases in Blueberry Bush Leaves},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR},
year={2023},
pages={355-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012207100003598},
isbn={978-989-758-671-2},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR
TI - DrBerry: Detection of Diseases in Blueberry Bush Leaves
SN - 978-989-758-671-2
IS - 2184-3228
AU - Morales, C.
AU - Cavero, E.
AU - Ugarte, W.
PY - 2023
SP - 355
EP - 364
DO - 10.5220/0012207100003598
PB - SciTePress