228.

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Page 302


ture for a self-organising neural pattern recognition machine’, Computer Vision, Graphics, and Image Processing 37, 54–115.

——(1987b) ‘ART2: Stable self-organisation of pattern recognition codes for analog input patterns’, Applied Optics 26, 4919–30.

Carpenter, G.A., Grossberg, S and Rosen, D.B. (1991a) ‘Fuzzy ART: fast stable learning and categorisation of analog patterns by an adaptive resonance system’, Neural Networks 4, 759–71.

Carpenter, G.A., Grossberg, S and Reynolds, J.H. (1991b) ‘ARTMAP: superviser real-time learning and classification of nonstationary data by a self-organising neural network’, Neural Networks 4, 565–88.

Carpenter, G.A., Grossberg, S., Markuzon, N., Reynolds, J.H. and Rosen, D.B. (1992) ‘Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps’, IEEE Transactions on Neural Networks 3, 698–713.

Carpenter, G.A., Gjaja, M.N., Gopal, S. and Woodcock, C.E. (1997) ‘ART neural networks for remote sensing: vegetation classification from Landsat TM and terrain data’, IEEE Transactions on Geoscience and Remote Sensing 33, 308–25.

Carr, J.R. (1996) ‘Spectral and textural classification of single and multiple band images’, Computers and Geosciences 22, 849–65.

——(1999) ‘Classification of digital image texture using variograms’, in P.M.Atkinson and N.J.Tate (eds) Advances in Remote Sensing and GIS Analysis. Chichester: John Wiley, pp. 135–46.

Carr, J.R. and Miranda, F.P. (1998) ‘The semivariogram in comparison to the co-occurrence matrix for classification of image texture’, IEEE Transactions on Geoscience and Remote Sensing 36, 1945–52.

Chandler, D. (1987) Introduction to Modern Statistical Mechanics. Oxford: Oxford University Press.

Chavez, P.S. Jr. (1988) ‘An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data’, Remote Sensing of Environment 24, 459–79.

Chica-Olmo, M. and Abarca-Hérnandez, F. (2000) ‘Computing geostatistical image texture for remotely sensed data classification’, Computers and Geosciences 26, 373–83.

Civco, D. (1989) ‘Topographic normalisation of Landsat Thematic Mapper imagery’, Photogrammetric Engineering and Remote Sensing 55, 1303–9.

Clarke, K.C. (1986) ‘Computation of the fractal dimension of topographic surfaces using the triangular prism surface area method’, Computers and Geosciences 12, 713–22.

Clausi, M. and Jernigan, M. (1998) ‘A fast method to determine co-occurrence texture features’, IEEE Transactions on Geoscience and Remote Sensing 36, 298–300.

Cochran, W.G. (1977) Sampling Techniques. New York: John Wiley.

Cohen, J. (1960) ‘A coefficient of agreement for nominal scales’, Educational and Psychological Measurement 20(1), 37–46.

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

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