Cluster kernels for semisupervised classification of VHR urban images

Details

Serval ID
serval:BIB_3A8DE69092A2
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Cluster kernels for semisupervised classification of VHR urban images
Title of the conference
Joint Urban Remote Sensing Event JURSE
Author(s)
Tuia D., Camps-Valls G.
ISBN
978-1-4244-3461-9
Publication state
Published
Issued date
2009
Peer-reviewed
Oui
Pages
1-5
Language
english
Notes
Tuia2009h
Abstract
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.
Create date
25/11/2013 17:18
Last modification date
20/08/2019 13:30
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