Land-cover classification through sequential learning-based optimum-path forest
Abstract
Sequential learning-based pattern classification aims at providing more accurate labeled maps by adding an extra step of classification using an augmented feature vector. In this paper, we evaluated the robustness of Optimum-Path Forest (OPF) classifier in the context of land-cover classification using both satellite and radar images, showing OPF can benefit from sequential learning theoretical basis.
How to cite this document
Pereira, D. et al. Land-cover classification through sequential learning-based optimum-path forest. International Geoscience and Remote Sensing Symposium (IGARSS), v. 2015-November, p. 76-79. Available at: <http://hdl.handle.net/11449/220599>.
Language
English
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