Abstract
This paper presents several strategies developed for classification of terrain regions, based on the SPRT algorithm (Sequential Probability Ratio Test [1]). The SPRT algorithm is considered to be appropriate to two-class-classification and will be extended by the introduced strategies for resolution of multi-class-classification problems. A comparison between the classifiers is made and the classification scores are shown for statistic synthetic patterns as well as for remote sensing data taken from an aerial view over cultivated regions.
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Reference
K.S. Fu, Sequential Methods in Pattern Recognition and Machine Learning, Academic Press, New York, 1968.
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© 1991 Springer-Verlag Berlin Heidelberg
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Huang, Y., Zamperoni, P. (1991). Terrain Classification by Sequential Algorithms. In: Radig, B. (eds) Mustererkennung 1991. Informatik-Fachberichte, vol 290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-08896-8_30
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DOI: https://doi.org/10.1007/978-3-662-08896-8_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-54597-2
Online ISBN: 978-3-662-08896-8
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