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Date fruit dataset for intelligent harvesting

The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no p...

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Detalles Bibliográficos
Autores principales: Altaheri, Hamdi, Alsulaiman, Mansour, Muhammad, Ghulam, Amin, Syed Umar, Bencherif, Mohamed, Mekhtiche, Mohamed
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811983/
https://www.ncbi.nlm.nih.gov/pubmed/31667277
http://dx.doi.org/10.1016/j.dib.2019.104514
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author Altaheri, Hamdi
Alsulaiman, Mansour
Muhammad, Ghulam
Amin, Syed Umar
Bencherif, Mohamed
Mekhtiche, Mohamed
author_facet Altaheri, Hamdi
Alsulaiman, Mansour
Muhammad, Ghulam
Amin, Syed Umar
Bencherif, Mohamed
Mekhtiche, Mohamed
author_sort Altaheri, Hamdi
collection PubMed
description The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no public dataset for date fruits to aid in this. In this work, we present a comprehensive dataset for date fruits that can be used by the research community for multiple tasks including automated harvesting, visual yield estimation, and classification tasks. The dataset contains images of date fruit bunches of different date varieties, captured at different pre-maturity and maturity stages. These images cover multiple sets of variations such as multi-scale images, variable illumination, and different bagging states. We also marked date bunches for selected palms and measured the weights of the bunches, captured their images on a graph paper, and recorded 360° video of the palms. This dataset can help in advancing research and automating date palm agricultural applications, including robotic harvesting, fruit detection and classification, maturity analysis, and weight/yield estimation. The dataset is freely and publicly available for the research community in the IEEE DataPort repository [1] (https://doi.org/10.21227/x46j-sk98).
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spelling pubmed-68119832019-10-30 Date fruit dataset for intelligent harvesting Altaheri, Hamdi Alsulaiman, Mansour Muhammad, Ghulam Amin, Syed Umar Bencherif, Mohamed Mekhtiche, Mohamed Data Brief Computer Science The date palm is one of the most valuable fruit trees in the world. Most methods used for date fruit inspection, harvesting, grading, and classification are manual, which makes them ineffective in terms of both time and economy. Research on automated date fruit harvesting is limited as there is no public dataset for date fruits to aid in this. In this work, we present a comprehensive dataset for date fruits that can be used by the research community for multiple tasks including automated harvesting, visual yield estimation, and classification tasks. The dataset contains images of date fruit bunches of different date varieties, captured at different pre-maturity and maturity stages. These images cover multiple sets of variations such as multi-scale images, variable illumination, and different bagging states. We also marked date bunches for selected palms and measured the weights of the bunches, captured their images on a graph paper, and recorded 360° video of the palms. This dataset can help in advancing research and automating date palm agricultural applications, including robotic harvesting, fruit detection and classification, maturity analysis, and weight/yield estimation. The dataset is freely and publicly available for the research community in the IEEE DataPort repository [1] (https://doi.org/10.21227/x46j-sk98). Elsevier 2019-09-18 /pmc/articles/PMC6811983/ /pubmed/31667277 http://dx.doi.org/10.1016/j.dib.2019.104514 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Altaheri, Hamdi
Alsulaiman, Mansour
Muhammad, Ghulam
Amin, Syed Umar
Bencherif, Mohamed
Mekhtiche, Mohamed
Date fruit dataset for intelligent harvesting
title Date fruit dataset for intelligent harvesting
title_full Date fruit dataset for intelligent harvesting
title_fullStr Date fruit dataset for intelligent harvesting
title_full_unstemmed Date fruit dataset for intelligent harvesting
title_short Date fruit dataset for intelligent harvesting
title_sort date fruit dataset for intelligent harvesting
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811983/
https://www.ncbi.nlm.nih.gov/pubmed/31667277
http://dx.doi.org/10.1016/j.dib.2019.104514
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