Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification

Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification

The principles of the creation of pattern recognition models, based on using multispectral imagery of forest land, have been analyzed. The statistical non-parametric model has been suggested as a basic pattern recognition model and the probability density function - as a recognition feature. Efficie...

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Main Authors: Guk Aleksander P., Evstratova Larisa G.
Format: Article
Language:English
Published: EDP Sciences 2019-01-01
Series:E3S Web of Conferences
Online Access:https://doi.org/10.1051/e3sconf/20197501002
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spelling doaj-ba7580011c364f74b3dae7456e3b501c2021-02-02T08:56:33ZengEDP SciencesE3S Web of Conferences2267-12422019-01-01750100210.1051/e3sconf/20197501002e3sconf_rpers2018_01002Research of efficiency of the statistical non-parametric pattern recognition models for forest land classificationGuk Aleksander P.Evstratova Larisa G.The principles of the creation of pattern recognition models, based on using multispectral imagery of forest land, have been analyzed. The statistical non-parametric model has been suggested as a basic pattern recognition model and the probability density function - as a recognition feature. Efficiency of the different quality criteria has been discussed. The main directions for improving the pattern recognition models are regarded.https://doi.org/10.1051/e3sconf/20197501002
collection DOAJ
language English
format Article
sources DOAJ
author Guk Aleksander P.
Evstratova Larisa G.
spellingShingle Guk Aleksander P.
Evstratova Larisa G.
Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
E3S Web of Conferences
author_facet Guk Aleksander P.
Evstratova Larisa G.
author_sort Guk Aleksander P.
title Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
title_short Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
title_full Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
title_fullStr Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
title_full_unstemmed Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
title_sort research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2019-01-01
description The principles of the creation of pattern recognition models, based on using multispectral imagery of forest land, have been analyzed. The statistical non-parametric model has been suggested as a basic pattern recognition model and the probability density function - as a recognition feature. Efficiency of the different quality criteria has been discussed. The main directions for improving the pattern recognition models are regarded.
url https://doi.org/10.1051/e3sconf/20197501002
work_keys_str_mv AT gukaleksanderp researchofefficiencyofthestatisticalnonparametricpatternrecognitionmodelsforforestlandclassification
AT evstratovalarisag researchofefficiencyofthestatisticalnonparametricpatternrecognitionmodelsforforestlandclassification
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