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Volumn 37, Issue 2 II, 1999, Pages 1179-1184

A technique for the selection of kernel-function parameters in rbf neural networks for classification of remote-sensing images

Author keywords

Image analysis; Neural networks; Pattern analysis; Remote sensing

Indexed keywords

ERROR ANALYSIS; ERROR CORRECTION; IMAGE ANALYSIS; MEMBERSHIP FUNCTIONS; NEURAL NETWORKS; PATTERN RECOGNITION;

EID: 0033099197     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/36.752239     Document Type: Article
Times cited : (150)

References (13)
  • 13
    • 0030291988 scopus 로고    scopus 로고
    • An experimental comparison of neural and statistical nonparametric algorithms for supervised classification of remote-sensing images
    • S. B. Serpico L. Bruzzone and F. Roll An experimental comparison of neural and statistical nonparametric algorithms for supervised classification of remote-sensing images Pattern Recognit. Lett. vol. 17 no. 13 pp. 1331-1341 1996.
    • Pattern Recognit. Lett. Vol. 17 No. 13 Pp. 1331-1341 1996.
    • Serpico, S.B.1    Bruzzone, L.2    Roll, F.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.