An incremental learning classifier for remote-sensing images

Author

Burzzone, L. ; Prieto, Diego Fernàndez ; Cossu, Roberto

Author_Institution

Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy

Volume

5

fYear

1999

fDate

1999

Firstpage

2483

Abstract

An incremental learning classifier based on RBF neural networks is presented. The proposed classifier relies on an incremental learning technique that allows the periodical acquisition of new knowledge when new training sets became available, without suffering a significant loss of the existing one. Such a characteristic renders the presented classifier a promising tool for the monitoring of extended geographical areas in a regular basis

Keywords

geophysical signal processing; geophysical techniques; geophysics computing; image classification; knowledge engineering; learning (artificial intelligence); radial basis function networks; remote sensing; terrain mapping; RBF neural network; geophysical measurement technique; image classification; imaging; incremental learning classifier; knowledge acquisition; land surface; neural net; neural network; periodical acquisition; radial basis function; remote sensing; remote-sensing image; terrain mapping; training set; Computer architecture; Costs; Electronic mail; Kernel; Neural networks; Neurons; Remote monitoring; Remote sensing; Rendering (computer graphics); Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International

Conference_Location

Hamburg

Print_ISBN

0-7803-5207-6

Type

conf

DOI

10.1109/IGARSS.1999.771550

Filename

771550