E3S Web Conf.
Volume 75, 2019Regional Problems of Earth Remote Sensing (RPERS 2018)
|Number of page(s)||5|
|Section||Methods and Algorithms for Image Processing|
|Published online||14 January 2019|
Research of efficiency of the statistical non-parametric pattern recognition models for forest land classification
Siberian State University of Geosystems and Technologies, 630018, 10 Plakhotnogo Str., Novosibirsk, Russian Federation
2 State University of Land Use Planning, 105064, 15 Kazakova str, Moscow, Russian Federation
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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