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Journal of Automation and Information Sciences

Published 12 issues per year

ISSN Print: 1064-2315

ISSN Online: 2163-9337

SJR: 0.173 SNIP: 0.588 CiteScore™:: 2

Indexed in

Methodology of Accuracy Assessment of Classification of Objects on Space Images

Volume 39, Issue 1, 2007, pp. 48-55
DOI: 10.1615/J Automat Inf Scien.v39.i1.50
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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.

CITED BY
  1. Popov Mykhailo, Michaelides Silas, Stankevich Sergey, Kozlova Anna, Piestova Iryna, Lubskiy Mykola, Titarenko Olga, Svideniuk Mykhailo, Andreiev Artem, Ivanov Serguei, Assessing long-term land cover changes in watershed by spatiotemporal fusion of classifications based on probability propagation: The case of Dniester river basin, Remote Sensing Applications: Society and Environment, 22, 2021. Crossref

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