@inproceedings{51a8bbdaba9c46f997ff65d01e98e6c4,
title = "DrBerry: Detection of Diseases in Blueberry Bush Leaves",
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.",
keywords = "Blueberry, Computer Vision, Disease, Machine Learning, Plague, YoloV5",
author = "Cristopher Morales and Edgar Cavero and Willy Ugarte",
note = "Publisher Copyright: Copyright {\textcopyright} 2023 by SCITEPRESS - Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0); 15th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K 2023 ; Conference date: 13-11-2023 Through 15-11-2023",
year = "2023",
doi = "10.5220/0012207100003598",
language = "Ingl{\'e}s",
series = "International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, IC3K - Proceedings",
publisher = "Science and Technology Publications, Lda",
pages = "355--364",
editor = "Ana Fred and Frans Coenen and Jorge Bernardino",
booktitle = "15th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2023 as part of IC3K 2023 - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management",
}