RVM-based multi-class classification of remotely sensed data

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RVM-based multi-class classification of remotely sensed data

The relevance vector machine (RVM), a Bayesian extension of the support vector machine (SVM), has considerable potential for the analysis of remotely sensed data. Here, the RVM is introduced and used to derive a multi-class classification of land cover with an accuracy of 91.25%, a level comparable...

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Bibliographic Details
Main Author:	Foody, Giles M.
Format:	Article
Published:	Taylor & Francis 2008
Online Access:	https://eprints.nottingham.ac.uk/1997/

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