A technique for the selection of kernel-function parameters in RBF neural networks for classification of remote-sensing images
- 1 March 1999
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Geoscience and Remote Sensing
- Vol. 37 (2), 1179-1184
- https://doi.org/10.1109/36.752239
Abstract
No abstract availableKeywords
This publication has 9 references indexed in Scilit:
- Strategies and best practice for neural network image classificationInternational Journal of Remote Sensing, 1997
- An experimental comparison of neural and statistical non-parametric algorithms for supervised classification of remote-sensing imagesPattern Recognition Letters, 1996
- Neural Networks for Pattern RecognitionPublished by Oxford University Press (OUP) ,1995
- A review and analysis of backpropagation neural networks for classification of remotely-sensed multi-spectral imageryInternational Journal of Remote Sensing, 1995
- Classification and feature extraction of AVIRIS dataIEEE Transactions on Geoscience and Remote Sensing, 1995
- Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing DataIEEE Transactions on Geoscience and Remote Sensing, 1990
- Parallel, self-organizing, hierarchical neural networksIEEE Transactions on Neural Networks, 1990
- Fast Learning in Networks of Locally-Tuned Processing UnitsNeural Computation, 1989
- On the capabilities of multilayer perceptronsJournal of Complexity, 1988