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...

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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Data Article
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
Descripción
Sumario: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.

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