The effectiveness of non-parametric classifiers in a limited training set
Автор: Romanov Aleksey A., Rubanov Kirill A.
Журнал: Журнал Сибирского федерального университета. Серия: Техника и технологии @technologies-sfu
Статья в выпуске: 5 т.5, 2012 года.
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This paper presents a comparative analysis of the effectiveness of the method of support vector machine and artificial neural networks for classification of satellite images medium spatial resolution as an example of a high degree of heterogeneity and limited training data. The results of field-based researches have been used for test cases generation. Neural network approach showed the best result for classification accuracy (89,9 % vs. 86,2 % support vector), but was significantly less speed.
Remote sensing, pattern recognition, supervised classification, neural networks, support vector machine
Короткий адрес: https://sciup.org/146114672
IDR: 146114672