Support Vector Machine]
||D. Tuia and G.
||Full Matlab Package|
|Code for the paper (please cite it!)
||Semi-supervised Remote Sensing Image
Classification with Cluster Kernels
Devis Tuia and Gustavo Camps-Valls
IEEE Geoscience and Remote Sensing Letters, 6 (2), 224-228, 2009.
semi-supervised SVM is presented for the classification of remote
sensing images. The method exploits the wealth of unlabeled samples for
regularizing the training kernel representation locally by means of
cluster kernels. The method learns
a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using
a predefined kernel structure. Good results are obtained in image
classification examples when few labeled samples are available. The
method scales almost linearly with the number of unlabeled samples and
provides out-of-sample predictions.
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