Abstract
Multisource classification methods based on neural networks, statistical modeling, genetic algorithms, and fuzzy methods are considered. For most of these methods, the individual data sources are at first treated separately and modeled by statistical methods. Then several decision fusion schemes are applied to combine the information from the individual data sources. These schemes include weighted consensus theory where the weights of the individual data sources reflect the reliability of the sources. The weights are optimized in order to improve the combined classification accuracies. The methods are applied in the classification of a multisource data set, and the results compared to accuracies obtained with conventional classification schemes.
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References
Benediktsson, J.A., Swain, P.H.: Consensus theoretic classification methods. IEEE Transactions on Systems Man and Cybernetics. 22 (1992) 688–704.
Kanellopoulos, I., Fierens, F., Wilkinson, G.G.: Combination of parametric and neural classifiers for analysis of multi-sensor Remote Sensing imagery. Neural and Stochastic Methods in Image and Signal Processing III (Edited by Su-Shing Chen), Proceedings SPIE 2304 (1994).
Serpico S.B. Roli, F.: Classification of multisensor remote-sensing images by structured neural networks. IEEE Transactions on Geoscience and Remote Sensing. 33(1995) 562–578.
Solberg, A.H.: Contextual Data Fusion Applied to Forest Map Revision. IEEE Transactions on Geoscience and Remote Sensing. 37 (1999) 1234–1243.
Benediktsson, J.A. Sveinsson, J.R., Swain, P.H.: Hybrid consensus theoretic classification. IEEE Transactions on Geoscience and Remote Sensing. 35 (1997) 833–843.
Benediktsson, J.A., Sveinsson, J.R., Ersoy, O.K., Swain, P.H.: Parallel Consensual Neural Networks. IEEE Transactions on Neural Networks. 8 (1997) 54–65.
Ruck, D.W., Rogers, S.K., Kabrisky, M., Oxley, M.E., Suter, B.W.: The multilayer perceptron as an approximation to a Bayes optimal discrimination function. IEEE Transactions on Neural Networks. 1 (1990) 296–298..
Mani, G.: Lowering Variance of decisions by using artificial neural network portfolios. Neural Computation. 3 (1991) 484–486.
Coifman, R.R., Wickerhauser, M.V.: Entropy-based algorithms for best basis selection. IEEE Transactions on Information Theory 38 (1992) 713–718.
Larsen, J., Svarer, C., Nonboe Andersen, L., Hansen, L.K.: Adaptive regularization in neural network modeling. Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science 1524. Springer-Verlag, Berlin (1998) 113–132.
Nonboe Andersen, L., Larsen, J., Hansen, L.K., Hintz-Madsen, M.: Adaptive regularization of neural classifiers. Proceedings of the IEEE Workshop on Neural Networks for Signal Processing VII. IEEE Press, Piscataway (1997).
Michalewicz Z.: Genetic Algorithms + Data Structures = Evolution Programs, Third, Revised and Extended and Edition, Springer-Verlag, New York (1995).
Yao, L., Seathers, W.A.: Nonlinear parameter estimation via the genetic algorithm. IEEE Transactions on Signal Processing 42(1994) 927–935.
Cho, S-B, Kim, J.H.: Multiple network fusion using fuzzy logic. IEEE Transactions on Neural Networks 6 (1995) 497–501.
Kosko, B.: Neural Networks and Fuzzy Systems, A Dynamical Systems Approach to Machine Intelligence. Prentice Hall, Englewood Cliffs, N.J. (1992).
Richards, J.A., Jia, X.: Remote Sensing Digital Image Analysis, An Introduction. Third, Revised and Enlarged Edition. Springer-Verlag, Berlin (1999).
Benediktsson, J.A., Benediktsson K. Hybrid consensus theoretic classification with pruning and regularization, Proceedings of the 1999 International Geoscience and Remote Sensing Symposium (IGARSS’ 99). Hamburg, Germany (1999) 2486–2488.
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Benediktsson, J.A., Sveinsson, J.R. (2000). Consensus Based Classification of Multisource Remote Sensing Data. In: Multiple Classifier Systems. MCS 2000. Lecture Notes in Computer Science, vol 1857. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45014-9_27
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DOI: https://doi.org/10.1007/3-540-45014-9_27
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