Crop classification by a support vector machine with intelligently selected training data for an operational application
The accuracy of supervised classification is dependent to a large extent on the training data used. The aim is often to capture a large training set to fully describe the classes spectrally, commonly with the requirements of a conventional statistical classifier in-mind. However, it is not always ne...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis
2008
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| Online Access: | http://eprints.nottingham.ac.uk/1996/ http://eprints.nottingham.ac.uk/1996/ http://eprints.nottingham.ac.uk/1996/ http://eprints.nottingham.ac.uk/1996/1/ePrints-Crop-IJRS_2008.pdf |