Инд. авторы:	Berikov V.B., Pestunov I.A., Karaev N.M., Tewari A.
Заглавие:	Recognition of hyperspectral images with use of cluster ensemble and semisupervised learning
Библ. ссылка:	Berikov V.B., Pestunov I.A., Karaev N.M., Tewari A. Recognition of hyperspectral images with use of cluster ensemble and semisupervised learning // CEUR Workshop Proceedings. - 2017. - Vol.2033. - P.60-64. - ISSN 1613-0073.
Внешние системы:	РИНЦ: 35531461; SCOPUS: 2-s2.0-85040226054;
Реферат:	eng: We suggest a method for hyperspectral image analysis on the basis of semi-supervised learning. The main idea is to divide the process of training of a classifier into two stages. First of all, with usage of cluster ensemble algorithms, variants of image segmentation are obtained. On their basis, the averaged co-Association matrix is calculated. On the second stage, a classifier is constructed on labeled pixels using similarity based learning algorithms with the given matrix as input. An example of the application of the method for analysis of hyperspectral images is given. It is shown that the suggested algorithm is more robust to noise than the standard support vector machine method.
Ключевые слова:	Hyperspectral image; Learning by similarity; Learning algorithms; Support vector machine method; Semi- supervised learning; Learning by similarity; Labeled pixels; Co-association matrix; Cluster ensembles; Supervised learning; Spectroscopy; Monitoring; Matrix algebra; Independent component analysis; Image segmentation; Image analysis; Hyperspectral imaging; Data handling; Clustering algorithms; Cluster ensemble; Semi-supervised learning;
Издано:	2017
Физ. характеристика:	с.60-64
Конференция:	Название: XIV Всероссийская научная конференция «Электронные библиотеки: перспективные методы и технологии, электронные коллекции» Аббревиатура: RCDL`2012 Город: Переславль-Залесский Страна: Россия Даты проведения: 2012-10-15 - 2012-10-18 Ссылка: http://rcdl2012.pereslavl.ru