Spectral angle based kernels for the classification of hyperspectral images using support vector machines
Support vector machines (SVM) have been extensively used for classification purposes in a broad range of applications. These learning machines base their classification on the Euclidean distance of the data vectors or their dot products. These measures do not account for the spectral signature infor...
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Main Authors: | , |
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Format: | Book Section |
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Institute of Electrical and Electronics Engineers
2008
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Online Access: | http://eprints.utm.my/id/eprint/12764/ http://dx.doi.org/10.1109/AMS.2008.152 |
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