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Post-harvested Musa acuminata Banana Tiers Dataset

Post-harvested Musa acuminata banana species from a local banana plantation in the Philippines are the subject of this article. All banana tier samples used were pre-classified into four classes by a local expert. These four classifications are extra class, class I, class II, and reject. There are s...

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Detalles Bibliográficos
Autores principales: Piedad, Eduardo Jr, Caladcad, June Anne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823153/
https://www.ncbi.nlm.nih.gov/pubmed/36624762
http://dx.doi.org/10.1016/j.dib.2022.108856
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author Piedad, Eduardo Jr
Caladcad, June Anne
author_facet Piedad, Eduardo Jr
Caladcad, June Anne
author_sort Piedad, Eduardo Jr
collection PubMed
description Post-harvested Musa acuminata banana species from a local banana plantation in the Philippines are the subject of this article. All banana tier samples used were pre-classified into four classes by a local expert. These four classifications are extra class, class I, class II, and reject. There are six images captured per banana tier sample from the six different views. Each captured image underwent a three-step image transformation to finely extract the RGB numerical values while the size measurement feature was gathered through manual measurement. The dataset presented in this article provides a brief differentiation of the different classes of banana tiers for commercial use through image processing. This dataset can be useful in establishing an advanced intelligent system in a non-invasive approach through machine and deep learning techniques.
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spelling pubmed-98231532023-01-08 Post-harvested Musa acuminata Banana Tiers Dataset Piedad, Eduardo Jr Caladcad, June Anne Data Brief Data Article Post-harvested Musa acuminata banana species from a local banana plantation in the Philippines are the subject of this article. All banana tier samples used were pre-classified into four classes by a local expert. These four classifications are extra class, class I, class II, and reject. There are six images captured per banana tier sample from the six different views. Each captured image underwent a three-step image transformation to finely extract the RGB numerical values while the size measurement feature was gathered through manual measurement. The dataset presented in this article provides a brief differentiation of the different classes of banana tiers for commercial use through image processing. This dataset can be useful in establishing an advanced intelligent system in a non-invasive approach through machine and deep learning techniques. Elsevier 2022-12-25 /pmc/articles/PMC9823153/ /pubmed/36624762 http://dx.doi.org/10.1016/j.dib.2022.108856 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Piedad, Eduardo Jr
Caladcad, June Anne
Post-harvested Musa acuminata Banana Tiers Dataset
title Post-harvested Musa acuminata Banana Tiers Dataset
title_full Post-harvested Musa acuminata Banana Tiers Dataset
title_fullStr Post-harvested Musa acuminata Banana Tiers Dataset
title_full_unstemmed Post-harvested Musa acuminata Banana Tiers Dataset
title_short Post-harvested Musa acuminata Banana Tiers Dataset
title_sort post-harvested musa acuminata banana tiers dataset
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823153/
https://www.ncbi.nlm.nih.gov/pubmed/36624762
http://dx.doi.org/10.1016/j.dib.2022.108856
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