NDLI: Radial basis function for classification of remote sensing images

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Radial basis function for classification of remote sensing images

Content Provider	IEEE Xplore Digital Library
Author	Bastos, L.C. Bastos, R.C. Nishida, W.
Copyright Year	1999
Description	Author affiliation: Centro Tecnologico, Univ. Federal de Santa Catarina, Florianapolis, Brazil (Bastos, L.C.)
Abstract	This work presents a hybrid classifier for multispectral images using radial basis function networks (RBF). A Kohonen self-organization-map is used in substitution of the k-means algorithm in unsupervised stage of training. The algorithm of the pseudo-inverse is used for the determination of the weights of the supervised stage. The architecture proposed reduces the time required for processing. Also, it presents satisfactory results with small training samples. A practical application is accomplished and the results obtained between the classifier of maximum likelihood and the proposed hybrid classifier are compared.
Starting Page	1959
Ending Page	1962
File Size	287994
Page Count	4
File Format	PDF
ISBN	0780355296
ISSN	10987576
DOI	10.1109/IJCNN.1999.832683
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-07-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Remote monitoring Vegetation mapping Artificial neural networks Multispectral imaging Artificial intelligence Testing Radial basis function networks Management training Resource management
Content Type	Text
Resource Type	Article

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