Cluster kernels for semisupervised classification of VHR urban images

Détails

ID Serval
serval:BIB_3A8DE69092A2
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Cluster kernels for semisupervised classification of VHR urban images
Titre de la conférence
Joint Urban Remote Sensing Event JURSE
Auteur(s)
Tuia D., Camps-Valls G.
ISBN
978-1-4244-3461-9
Statut éditorial
Publié
Date de publication
2009
Peer-reviewed
Oui
Pages
1-5
Langue
anglais
Notes
Tuia2009h
Résumé
In this paper, we present and apply a semisupervised support vector
machine based on cluster kernels for the problem of very high resolution
image classification. In the proposed setting, a base kernel working
with labeled samples only is deformed by a likelihood kernel encoding
similarities between unlabeled examples. The resulting kernel is
used to train a standard support vector machine (SVM) classifier.
Experiments carried out on very high resolution (VHR) multispectral
and hyperspectral images using very few labeled examples show the
relevancy of the method in the context of urban image classification.
Its simplicity and the small number of parameters involved make it
versatile and workable by unexperimented users.
Création de la notice
25/11/2013 18:18
Dernière modification de la notice
20/08/2019 14:30
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