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Auteur Rodrigo José Pisani |
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Toward satellite-based land cover classification through optimum-path forest / Rodrigo José Pisani in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
[article]
Titre : Toward satellite-based land cover classification through optimum-path forest Type de document : Article/Communication Auteurs : Rodrigo José Pisani, Auteur ; Rodrigo Yuji Mizobe Nakamura, Auteur ; Paulina Setti Riedel, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 6075 - 6085 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] forêt
[Termes IGN] occupation du solRésumé : (Auteur) Land cover classification has been paramount in the last years. Since the amount of information acquired by satellite on-board imaging systems has increased, there is a need for automatic tools that can tackle such problem. Despite the fact that one can find several works in the literature, we propose a novel methodology for land cover classification by means of the optimum-path forest (OPF) framework, which has never been applied to this context up to date. Experiments were conducted in supervised and unsupervised situations against some state-of-the-art pattern recognition techniques, such as support vector machines, Bayesian classifier, k-means, and mean shift. We had shown that supervised OPF can outperform such approaches, being much faster than all. In regard to clustering techniques, all classifiers have achieved similar results. Numéro de notice : A2014-483 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2294762 En ligne : https://doi.org/10.1109/TGRS.2013.2294762 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74066
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6075 - 6085[article]Exemplaires(1)
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