Инд. авторы:	Pestunov I., Rylov S., Berikov V.
Заглавие:	Hierarchical ensemble clustering algorithm for multispectral image segmentation
Библ. ссылка:	Pestunov I., Rylov S., Berikov V. Hierarchical ensemble clustering algorithm for multispectral image segmentation // 9th Open German-Russian Worokshop on Pattern Recognition and Image Understanding: Proceedings. - 2015: University of Koblenz-Landau in Koblenz. - P.123-127.
Внешние системы:	РИНЦ: 24087276;
Реферат:	eng: A novel hierarchical clustering algorithm based on nonparametric estimation of the global probability density function of the data points is proposed. Special similarity metric is introduced to deal with overlapping classes. Ensemble approach allows combining multiple hierarchical partitionings and improving the quality of results in exploring complicated hierarchical structures. High computing efficiency allowing interactive multispectral satellite image processing is achieved by the use of grid-based approach. Experimental results on both synthetic and real datasets demonstrate the effectiveness of the proposed algorithm.
Ключевые слова:	multispectral satellite images; fast image segmentation; hierarchical ensemble clustering; density-based approach; grid-based approach;
Издано:	2015
Физ. характеристика:	с.123-127
Конференция:	Название: 9-th Open German-Russian Workshop on PATTERN RECOGNITION and IMAGE UNDERSTANDING Аббревиатура: OGRW-9-2014 Город: Koblenz Страна: Germahy Даты проведения: 2014-12-01 - 2014-12-05 Ссылка: http://userpages.uni-koblenz.de/~ogrw2014/
Цитирование:	1. A. Pestunov, Yu.N. Sinyavsky, “Clustering algorithms in problems of segmentation of satellite images,” Bull. Kemerovo State Univ. 2012. No 4/2(52), pp. 110-125. 2. R. Xu, D.I. Wunsch, “Survey of clustering algorithms,” IEEE Trans. on Neural Networks. 2005. Vol. 16, N 3, pp. 645-678. 3. L. Zheng, T. Li, C. Ding, “Hierarchical Ensemble Clustering,” Proc. of 2011 IEEE Intern. Conf. on Data Mining. IEEE, 2010, pp. 1199-1204. 4. A. Mirzaei, M. Rahmati, “A novel hierarchical-clustering-combination scheme based on fuzzy-similarity relations,” IEEE Trans. Fuzzy Syst. 2010. Vol. 18, N 1, pp. 27-39. 5. I.A. Pestunov, V.B. Berikov, E.A. Kulikova, S.A. Rylov, “Ensemble of clustering algorithms for large datasets,” Optoelectronics, instrumentation and data processing. 2011. Vol. 47, N 3, pp. 245-252. 6. B. Leclerc, “Description combinatoire des ultramétriques,” Math. Sci. Humaines. 1981. Vol. 73, pp. 5-37. 7. E. Achtert, H. Kriegel, E. Schubert, A. Zimek, “Interactive Data Mining with 3D-Parallel-Coordinate-Trees,” Proc. ACM Intern. Conf. on Management of Data (SIGMOD). NY, 2013, pp. 1009-1012.