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Journal of Automation and Information Sciences
SJR: 0.232 SNIP: 0.464 CiteScore™: 0.27

ISSN Print: 1064-2315
ISSN Online: 2163-9337

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Volume 51, 2019 Volume 50, 2018 Volume 49, 2017 Volume 48, 2016 Volume 47, 2015 Volume 46, 2014 Volume 45, 2013 Volume 44, 2012 Volume 43, 2011 Volume 42, 2010 Volume 41, 2009 Volume 40, 2008 Volume 39, 2007 Volume 38, 2006 Volume 37, 2005 Volume 36, 2004 Volume 35, 2003 Volume 34, 2002 Volume 33, 2001 Volume 32, 2000 Volume 31, 1999 Volume 30, 1998 Volume 29, 1997 Volume 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/J Automat Inf Scien.v39.i1.50
pages 48-55

Methodology of Accuracy Assessment of Classification of Objects on Space Images

Mikhail A. Popov
Research Center of Aerospace Research of the Earth of the Institute of Geological Sciences of National Academy of Sciences of Ukraine, Kiev, Ukraine

ABSTRACT

The main aspects of improving the methodology of accuracy assessment of information received from space images are considered. The accuracy assessment criteria of classification of objects on the space images are discussed. Two statistic models for determining an examination sample size — binomial and polynomial are described. The influence of identification degree of pixels and geometry of examination site on classification accuracy is quantitatively evaluated. The particularities of accuracy assessment for classification of hyperspectral images are considered.


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