Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images-Reference-Cited by-同舟云学术

Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images

Published:2017-01 Issue:1 Volume:50 Page:144-154
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Raczko Edwin¹,Zagajewski Bogdan¹^ORCID

Affiliation:

1. University of Warsaw, Faculty of Geography and Regional Studies, Department of Geoinformatics, Cartography and Remote Sensing, Warsaw, Poland

Funder

Ecosystem stress from the combined effects of winter climate change and air pollution – how do the impacts differ between biomes? (WICLAP)

Polish Ministry of Sciences and Higher Education

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://tandfonline.com/doi/pdf/10.1080/22797254.2017.1299557

Reference54 articles.

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3. Classification of textures in satellite image with Gabor filters and a multi layer perceptron with back propagation algorithm obtaining high accuracy

4. Deterioration of forests in the Sudety Mountains, Poland, detected on satellite images

5. Is cross-validation valid for small-sample microarray classification?

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