Interpolation-based data augmentation using Gaussian processes with combined kernels improves regression accuracy for sugarcane weed coverage more efficiently than kriging, at the cost of spatial homogeneity.
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Interpolation pour l'augmentation de donnees : Application \`a la gestion des adventices de la canne a sucre a la Reunion
Interpolation-based data augmentation using Gaussian processes with combined kernels improves regression accuracy for sugarcane weed coverage more efficiently than kriging, at the cost of spatial homogeneity.