Article: article from journal or magazin.
Semi-supervised remote sensing image classification with cluster kernels
IEEE Geoscience and Remote Sensing Letters
A semisupervised support vector machine 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.
Bagged and cluster kernels, image classification, kernel methods, support vector (SV) machine (SVM)
Web of science
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