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https://doi.org/10.5194/ica-abs-6-50-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ica-abs-6-50-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
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11 Aug 2023
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11 Aug 2023
Crop classification and weed detection in rainfed maize crops using UAV and PlanetScope imagery
Colette de Villiers
,
Cilence Munghemezulu
,
George Johannes Chirima
,
Solomon G. Tesfamichael
,
and
Zinhle Mashaba-Munghemezulu
Colette de Villiers
×
Geoinformation Science Division, Agricultural Research Council Institute for Soil, Climate and Water, Pretoria 0001, South Africa
Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria 0028, South Africa
Cilence Munghemezulu
×
Geoinformation Science Division, Agricultural Research Council Institute for Soil, Climate and Water, Pretoria 0001, South Africa
George Johannes Chirima
×
Geoinformation Science Division, Agricultural Research Council Institute for Soil, Climate and Water, Pretoria 0001, South Africa
Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria 0028, South Africa
Solomon G. Tesfamichael
×
Geography Environmental Management Energy Studies, University of Johannesburg, Johannesburg 2006, South Africa
Zinhle Mashaba-Munghemezulu
×
Geoinformation Science Division, Agricultural Research Council Institute for Soil, Climate and Water, Pretoria 0001, South Africa
Keywords:
maize, weed detection, uav, planetscope, machine learning
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