Feature selection for classification of hyperspectral data by SVM
SVM are attractive for the classification of remotely sensed data with some claims that the method is insensitive to the dimensionality of the data and so not requiring a dimensionality reduction analysis in pre-processing. Here, a series of classification analyses with two hyperspectral sensor data...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers
2010
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| Online Access: | http://eprints.nottingham.ac.uk/1998/ http://eprints.nottingham.ac.uk/1998/ http://eprints.nottingham.ac.uk/1998/ http://eprints.nottingham.ac.uk/1998/1/ePrints-feature_selection-2010.pdf |