Fuzzy ARTMAP — A Neural Classifier for Multispectral Image Classification

Sucharita Gopal and Manfred Fischer
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Sucharita Gopal: Boston University

Chapter 16 in Recent Developments in Spatial Analysis, 1997, pp 306-335 from Springer

Abstract: Abstract Spectral pattern recognition deals with classifications that utilize pixel-by-pixel spectral information from satellite imagery. The literature on neural network applications in this area is relatively new, dating back only about six to seven years. The first studies established the feasibility of error-based learning systems such as backpropagation (see Key et al., 1989, McClellan et al., 1989, Benediktsson et al., 1990, Hepner et al., 1990). Subsequent studies analysed backpropagation networks in more detail and compared them to standard statistical classifiers such as the Gaussian maximum likelihood (see Bischof et al., 1992, Kanellopoulos et al., 1993, Fischer et al., 1994).

Keywords: Input Pattern; Adaptive Weight; Adaptive Resonance Theory; Fuzzy ARTMAP; ARTa Category (search for similar items in EconPapers)
Date: 1997
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DOI: 10.1007/978-3-662-03499-6_16

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