Инд. авторы:	Nezhevenko E.S., Feoktistov A.S., Dashevskii O.Y.
Заглавие:	Neural Network Classification of Hyperspectral Images on the Basis of the Hilbert-Huang Transform
Библ. ссылка:	Nezhevenko E.S., Feoktistov A.S., Dashevskii O.Y. Neural Network Classification of Hyperspectral Images on the Basis of the Hilbert-Huang Transform // Optoelectronics, Instrumentation and Data Processing. - 2017. - Vol.53. - Iss. 2. - P.165-170. - ISSN 8756-6990. - EISSN 1934-7944.
Внешние системы:	DOI: 10.3103/S8756699017020091; SCOPUS: 2-s2.0-85020550980; WoS: 000409138100009;
Реферат:	eng: The method of image classification with its preliminary transformation to principal components and with the use of the Hilbert-Huang transform is studied by an example of neural network classification of a hyperspectral image. The efficiency of the method is demonstrated through comparisons with traditional methods of neural network classification with the use of spectral components and principal components without involving spatial information as features. Radial-basis and complex neural networks are used for classification.
Ключевые слова:	complex neural networks; principal components; Hilbert-Huang transform; hyperspectral image; classification;
Издано:	2017
Физ. характеристика:	с.165-170