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...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis
2008
|
| Online Access: | http://eprints.nottingham.ac.uk/1997/ http://eprints.nottingham.ac.uk/1997/ http://eprints.nottingham.ac.uk/1997/ http://eprints.nottingham.ac.uk/1997/1/ePrints-RVM-IJRS_2008.pdf |