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: | , |
|---|---|
| Format: | Article |
| Published: |
Taylor & Francis
2008
|
| Online Access: | https://eprints.nottingham.ac.uk/1996/ |