CherryChèvre: A fine-grained dataset for goat detection in natural environments

We introduce a new dataset for goat detection that contains 6160 annotated images captured under varying environmental conditions. The dataset is intended for developing machine learning algorithms for goat detection, with applications in precision agriculture, animal welfare, behaviour analysis, an...

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Autores principales: Vayssade, Jehan-Antoine, Arquet, Rémy, Troupe, Willy, Bonneau, Mathieu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Data Descriptor
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567779/
https://www.ncbi.nlm.nih.gov/pubmed/37821512
http://dx.doi.org/10.1038/s41597-023-02555-8
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author Vayssade, Jehan-Antoine
Arquet, Rémy
Troupe, Willy
Bonneau, Mathieu
author_facet Vayssade, Jehan-Antoine
Arquet, Rémy
Troupe, Willy
Bonneau, Mathieu
author_sort Vayssade, Jehan-Antoine
collection PubMed
description We introduce a new dataset for goat detection that contains 6160 annotated images captured under varying environmental conditions. The dataset is intended for developing machine learning algorithms for goat detection, with applications in precision agriculture, animal welfare, behaviour analysis, and animal husbandry. The annotations were performed by expert in computer vision, ensuring high accuracy and consistency. The dataset is publicly available and can be used as a benchmark for evaluating existing algorithms. This dataset advances research in computer vision for agriculture.
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spelling pubmed-105677792023-10-13 CherryChèvre: A fine-grained dataset for goat detection in natural environments Vayssade, Jehan-Antoine Arquet, Rémy Troupe, Willy Bonneau, Mathieu Sci Data Data Descriptor We introduce a new dataset for goat detection that contains 6160 annotated images captured under varying environmental conditions. The dataset is intended for developing machine learning algorithms for goat detection, with applications in precision agriculture, animal welfare, behaviour analysis, and animal husbandry. The annotations were performed by expert in computer vision, ensuring high accuracy and consistency. The dataset is publicly available and can be used as a benchmark for evaluating existing algorithms. This dataset advances research in computer vision for agriculture. Nature Publishing Group UK 2023-10-11 /pmc/articles/PMC10567779/ /pubmed/37821512 http://dx.doi.org/10.1038/s41597-023-02555-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Data Descriptor
Vayssade, Jehan-Antoine
Arquet, Rémy
Troupe, Willy
Bonneau, Mathieu
CherryChèvre: A fine-grained dataset for goat detection in natural environments
title CherryChèvre: A fine-grained dataset for goat detection in natural environments
title_full CherryChèvre: A fine-grained dataset for goat detection in natural environments
title_fullStr CherryChèvre: A fine-grained dataset for goat detection in natural environments
title_full_unstemmed CherryChèvre: A fine-grained dataset for goat detection in natural environments
title_short CherryChèvre: A fine-grained dataset for goat detection in natural environments
title_sort cherrychèvre: a fine-grained dataset for goat detection in natural environments
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10567779/
https://www.ncbi.nlm.nih.gov/pubmed/37821512
http://dx.doi.org/10.1038/s41597-023-02555-8
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