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Development of maize plant dataset for intelligent recognition and weed control.

ABSTRACT: 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.

SUBMITTER: Olaniyi OM

PROVIDER: S-EPMC10018041 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature

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Development of maize plant dataset for intelligent recognition and weed control.

Olaniyi Olayemi Mikail OM Salaudeen Muhammadu Tajudeen MT Daniya Emmanuel E Abdullahi Ibrahim Mohammed IM Folorunso Taliha Abiodun TA Bala Jibril Abdullahi JA Nuhu Bello Kontagora BK Adedigba Adeyinka Peace AP Oluwole Blessing Israel BI Bankole Abdullah Oreoluwa AO Macarthy Odunayo Moses OM

Data in brief 20230301

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 hig ...[more]

PMID: 36936631

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