245.

[Cover] [Contents] [Index]

Page 318

Qattrochi, D.A. and Goodchild, M.A. (eds) (1997) Scale in Remote Sensing and GIS. New York: Lewis Publishers.

Quinlan, J.R. (1993) C4.5: Algorithm for Machine Learning. San Mateo: Morgan Kaufmann.

Ramstein, G. and Raffy, M. (1989) ‘Analysis of the structure of radiometric remotely-sensed images’, International Journal of Remote Sensing 10, 1049–73.

Raudys, S. and Pikelis, V. (1980) ‘On dimensionality, sample size, classification error, and complexity of classification algorithms in pattern recognition’, IEEE Transactions on Pattern Analysis and Machine Intelligence 2, 242–52.

Ray, T.W. and Murray, B.C. (1996) ‘Non-linear mixing in desert vegetation’, Remote Sensing of Environment 55, 59–64.

Reed, R. (1993) ‘Pruning algorithms—a survey’, IEEE Transactions on Neural Networks 4, 740–7.

Reeves, S.J. (1992) ‘A cross-validation framework for solving image restoration problems’, Journal of Visual Communication and Image Representation 3, 433–45.

Reilly, D.L., Cooper, L.N. and Elbaum, C. (1982) ‘A neural model for category learning’, Biological Cybernetics 45, 35–41.

Richards, J.A. (1986) Remote Sensing Digital Image Analysis—An Introduction. Berlin: Springer-Verlag.

Richards, J.A., Landgrebe, D.A. and Swain P.H. (1982) ‘A means for utilizing ancillary information in multispectral classification’, Remote Sensing of Environment 12, 463–77.

Ripley, B.D. (1996) Pattern Recognition and Neural Networks. Cambridge: Cambridge University Press.

Ritter, H. and Schulten, K. (1988) ‘Convergence properties of Kohonen’s topology conserving maps: fluctuations, stability and dimension selection’, Biological Cybernetics 60, 59–71.

Robinson, G.D., Gross, H.N. and Schott, J.R. (2000) ‘Evaluation of two applications of spectral unmixing models to image fusion’, Remote Sensing of Environment 71, 272–81.

Roli, F., Giacinto, G. and Vernazza, G. (1997) ‘Comparison and combination of statistical and neural net algorithms fore remote sensing image classification’, in I.Kanellopoulos, G.G.Wilkinson, G.G.Roli and J. Austin (eds) Neurocomputation in Remote Sensing Data Analysis. Berlin: Springer-Verlag, pp. 117–24.

Rosenblatt, R. (1959) Principles of Neurodynamics. New York: Spartan Books.

Rosenfield, G. (1982) ‘Analysis of variance of thematic mapping experiment data’, Photogrammetric Engineering and Remote Sensing 47, 1685–1692.

Rumelhart, D.E., Hinton, G.E. and Williams, R.J. (1986a) ‘Learning internal representation by error propagation’, Parallel Distributed Pro

[Cover] [Contents] [Index]


Classification Methods for Remotely Sensed Data
Classification Methods for Remotely Sensed Data, Second Edition
ISBN: 1420090720
EAN: 2147483647
Year: 2001
Pages: 354

flylib.com © 2008-2017.
If you may any questions please contact us: flylib@qtcs.net