Comparison of back propagation and binary diamond neural networks in the classification of a Landsat TM image

Computers and Geosciences

Volumn 22, Issue 9, 1996, Pages 995-1001

  Murnion, Shane D ^a  

^a UNIVERSITY OF PORTSMOUTH   (United Kingdom)

Author keywords

Multi layer; Perceptron; Real time; Remote sensing

Indexed keywords

BACK PROPAGATION; BINARY DIAMOND; CLASSIFICATION; IMAGE ANALYSIS; LANDSAT TM; NEURAL NETWORK;

JAPAN, HONSHU, KANAGAWA;

EID: 0030439210     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-3004(96)00037-4     Document Type: Article

References (6)

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3. McClelland, J. L., and Rumelhart, D. E., 1986, Parallel distributed processing: explorations in the microstructure of cognition, volumes 1 and 2: MIT Press, Cambridge, Massachusetts, 611 p.
4. Michie, D., Speigelhalter, D. J., and Taylor, C. C., 1994, Machine learning, neural and statistical classification: Prentice Hall Inc., Englewood Cliffs, New Jersey, 311 P.
5. Openshaw, S., 1993, Modelling spatial interaction using a neural net, in Fischer, M. M. and Nijkamp, P., eds., Geographic Information Systems, Spatial Modelling and Policy Evaluation: Springer-Verlag, London, p. 147-164.
6. Salu, Y., and Tilton, J., 1993, Classification of multispectral image data by the binary diamond neural network and by nonparametric, pixel-by-pixel methods: IEEE Trans. Geoscience and Remote Sensing, v. 31, no. 3, p. 606-617.