Cargando…
Development of maize plant dataset for intelligent recognition and weed control
This paper focuses on the development of maize plant datasets for the purposes of recognizing maize plants and weed species, as well as the precise automated application of herbicides to the weeds. The dataset includes 36,374 images captured with a high-resolution digital camera during the weed surv...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018041/ https://www.ncbi.nlm.nih.gov/pubmed/36936631 http://dx.doi.org/10.1016/j.dib.2023.109030 |
_version_ | 1784907725921058816 |
---|---|
author | Olaniyi, Olayemi Mikail Salaudeen, Muhammadu Tajudeen Daniya, Emmanuel Abdullahi, Ibrahim Mohammed Folorunso, Taliha Abiodun Bala, Jibril Abdullahi Nuhu, Bello Kontagora Adedigba, Adeyinka Peace Oluwole, Blessing Israel Bankole, Abdullah Oreoluwa Macarthy, Odunayo Moses |
author_facet | Olaniyi, Olayemi Mikail Salaudeen, Muhammadu Tajudeen Daniya, Emmanuel Abdullahi, Ibrahim Mohammed Folorunso, Taliha Abiodun Bala, Jibril Abdullahi Nuhu, Bello Kontagora Adedigba, Adeyinka Peace Oluwole, Blessing Israel Bankole, Abdullah Oreoluwa Macarthy, Odunayo Moses |
author_sort | Olaniyi, Olayemi Mikail |
collection | PubMed |
description | This paper focuses on the development of maize plant datasets for the purposes of recognizing maize plants and weed species, as well as the precise automated application of herbicides to the weeds. The dataset includes 36,374 images captured with a high-resolution digital camera during the weed survey and 500 images annotated with the Labelmg suite. Images of the eighteen farmland locations in North Central Nigeria, containing the maize plants and their associated weeds were captured using a high-resolution camera in each location. This dataset will serve as a benchmark for computer vision and machine learning tasks in the intelligent maize and weed recognition research. |
format | Online Article Text |
id | pubmed-10018041 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100180412023-03-17 Development of maize plant dataset for intelligent recognition and weed control Olaniyi, Olayemi Mikail Salaudeen, Muhammadu Tajudeen Daniya, Emmanuel Abdullahi, Ibrahim Mohammed Folorunso, Taliha Abiodun Bala, Jibril Abdullahi Nuhu, Bello Kontagora Adedigba, Adeyinka Peace Oluwole, Blessing Israel Bankole, Abdullah Oreoluwa Macarthy, Odunayo Moses Data Brief Data Article This paper focuses on the development of maize plant datasets for the purposes of recognizing maize plants and weed species, as well as the precise automated application of herbicides to the weeds. The dataset includes 36,374 images captured with a high-resolution digital camera during the weed survey and 500 images annotated with the Labelmg suite. Images of the eighteen farmland locations in North Central Nigeria, containing the maize plants and their associated weeds were captured using a high-resolution camera in each location. This dataset will serve as a benchmark for computer vision and machine learning tasks in the intelligent maize and weed recognition research. Elsevier 2023-03-01 /pmc/articles/PMC10018041/ /pubmed/36936631 http://dx.doi.org/10.1016/j.dib.2023.109030 Text en © 2023 The Author(s) https://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 | Data Article Olaniyi, Olayemi Mikail Salaudeen, Muhammadu Tajudeen Daniya, Emmanuel Abdullahi, Ibrahim Mohammed Folorunso, Taliha Abiodun Bala, Jibril Abdullahi Nuhu, Bello Kontagora Adedigba, Adeyinka Peace Oluwole, Blessing Israel Bankole, Abdullah Oreoluwa Macarthy, Odunayo Moses Development of maize plant dataset for intelligent recognition and weed control |
title | Development of maize plant dataset for intelligent recognition and weed control |
title_full | Development of maize plant dataset for intelligent recognition and weed control |
title_fullStr | Development of maize plant dataset for intelligent recognition and weed control |
title_full_unstemmed | Development of maize plant dataset for intelligent recognition and weed control |
title_short | Development of maize plant dataset for intelligent recognition and weed control |
title_sort | development of maize plant dataset for intelligent recognition and weed control |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10018041/ https://www.ncbi.nlm.nih.gov/pubmed/36936631 http://dx.doi.org/10.1016/j.dib.2023.109030 |
work_keys_str_mv | AT olaniyiolayemimikail developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT salaudeenmuhammadutajudeen developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT daniyaemmanuel developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT abdullahiibrahimmohammed developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT folorunsotalihaabiodun developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT balajibrilabdullahi developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT nuhubellokontagora developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT adedigbaadeyinkapeace developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT oluwoleblessingisrael developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT bankoleabdullahoreoluwa developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol AT macarthyodunayomoses developmentofmaizeplantdatasetforintelligentrecognitionandweedcontrol |