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Research Article

Comparison of Deep and Machine Learning Approaches for Quebec Tree Species Classification Using a Combination of Multispectral and LiDAR Data

Comparaison des approches d’apprentissage profond et d’apprentissage automatique pour la classification des espèces d’arbres du Québec à l’aide d’une combinaison de données multispectrales et LiDAR

Omid Reisi Gahroueia Digital Forest Lab, Department of Geomatics Sciences, Laval University, Quebec City, QCG1V 0A6, CanadaCorrespondence[email protected]
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Jean-François Côtéb Canadian Wood Fibre Centre, Canadian Forest Service, Natural Resources Canada, Québec City, QCG1V 4C7, CanadaView further author information

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Philippe Bournivalc Ministry of Natural Resources and Forests, 5700, 4ième Avenue Ouest, Québec City, QCG1H 6R1, CanadaView further author information

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Philippe Giguèred Department of Computer Science and Software Engineering, Université Laval, Québec City, QCG1V 0A6, CanadaView further author information

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Martin Bélanda Digital Forest Lab, Department of Geomatics Sciences, Laval University, Quebec City, QCG1V 0A6, CanadaView further author information