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1 Ergebnisse
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Modeling the spatial-spectral characteristics of plants for..:
Okyere, Frank Gyan
;
Cudjoe, Daniel
;
Sadeghi-Tehran, Pouria
...
Okyere FG, Cudjoe D, Sedaghi-Tehran P, et al., (2023) Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods. Frontiers in Plant Science, Volume 14, October 2023, Article number 1209500. , 2023
Link:
https://doi.org/10.3389/fpls.2023.1209500
RT Journal T1
Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods
UL https://suche.suub.uni-bremen.de/peid=base-ftcranfield:oai:dspace.lib.cranfield.ac.uk:1826_20414&Exemplar=1&LAN=DE A1 Okyere, Frank Gyan A1 Cudjoe, Daniel A1 Sadeghi-Tehran, Pouria A1 Virlet, Nicolas A1 Riche, Andrew B A1 Castle, March A1 Greche, Latifa A1 Simms, Daniel M A1 Mhada, Manal A1 Mohareb, Fady A1 Hawkesford, Malcolm John PB Frontiers YR 2023 K1 Convolution Neural Network K1 hyperspectral imaging K1 Plant Nutrition K1 machine learning K1 Spectral curves JF Okyere FG, Cudjoe D, Sedaghi-Tehran P, et al., (2023) Modeling the spatial-spectral characteristics of plants for nutrient status identification using hyperspectral data and deep learning methods. Frontiers in Plant Science, Volume 14, October 2023, Article number 1209500 LK http://dx.doi.org/https://doi.org/10.3389/fpls.2023.1209500 DO https://doi.org/10.3389/fpls.2023.1209500 SF ELIB - SuUB Bremen
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