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Combined classification of similar looking vegetative cover types using hyperspectral imagery. / Borzov, Sergey M.; Potaturkin, Oleg I.; Guryanov, Mark A.

в: CEUR Workshop Proceedings, Том 2033, 2017, стр. 65-67.

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Harvard

Borzov, SM, Potaturkin, OI & Guryanov, MA 2017, 'Combined classification of similar looking vegetative cover types using hyperspectral imagery', CEUR Workshop Proceedings, Том. 2033, стр. 65-67.

APA

Borzov, S. M., Potaturkin, O. I., & Guryanov, M. A. (2017). Combined classification of similar looking vegetative cover types using hyperspectral imagery. CEUR Workshop Proceedings, 2033, 65-67.

Vancouver

Borzov SM, Potaturkin OI, Guryanov MA. Combined classification of similar looking vegetative cover types using hyperspectral imagery. CEUR Workshop Proceedings. 2017;2033:65-67.

Author

Borzov, Sergey M. ; Potaturkin, Oleg I. ; Guryanov, Mark A. / Combined classification of similar looking vegetative cover types using hyperspectral imagery. в: CEUR Workshop Proceedings. 2017 ; Том 2033. стр. 65-67.

BibTeX

@article{256c4bb2311a4d4a9f828ab96473696e,
title = "Combined classification of similar looking vegetative cover types using hyperspectral imagery",
abstract = "In this paper we present an efficiency analysis of a number of methods for spectral and spectralspatial classification of similar looking vegetative cover types using hyperspectral images for different approaches to construction of the training set.",
keywords = "Hyperspectral images, Remote sensing, Spectral and spatial features, Surface type classification",
author = "Borzov, {Sergey M.} and Potaturkin, {Oleg I.} and Guryanov, {Mark A.}",
year = "2017",
language = "English",
volume = "2033",
pages = "65--67",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "CEUR-WS",

}

RIS

TY - JOUR

T1 - Combined classification of similar looking vegetative cover types using hyperspectral imagery

AU - Borzov, Sergey M.

AU - Potaturkin, Oleg I.

AU - Guryanov, Mark A.

PY - 2017

Y1 - 2017

N2 - In this paper we present an efficiency analysis of a number of methods for spectral and spectralspatial classification of similar looking vegetative cover types using hyperspectral images for different approaches to construction of the training set.

AB - In this paper we present an efficiency analysis of a number of methods for spectral and spectralspatial classification of similar looking vegetative cover types using hyperspectral images for different approaches to construction of the training set.

KW - Hyperspectral images

KW - Remote sensing

KW - Spectral and spatial features

KW - Surface type classification

UR - http://www.scopus.com/inward/record.url?scp=85040253355&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:85040253355

VL - 2033

SP - 65

EP - 67

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

ER -

ID: 9670884