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Decision fusion for the classification of hyperspectral data: outcome of the 2008 GRS-S Data Fusion Contest

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peer-reviewed

Veröffentlichung
2010-11-07
Authors
Licciardi, Giorgio
Pacifici, Fabio
Tuia, Devis
Prasad, Saurabh
West, Terrance
et al.
Wissenschaftlicher Artikel


Faculties
Fakultät für Ingenieurwissenschaften und Informatik
Abstract
The 2008 Data Fusion Contest organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee deals with the classification of high-resolution hyperspectral data from an urban area. Unlike in the previous issues of the contest, the goal was not only to identify the best algorithm but also to provide a collaborative effort: The decision fusion of the best individual algorithms was aiming at further improving the classification performances, and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, dimension reduction, and supervised classification methods, such as neural networks and support vector machines.
Date created
2009
Original publication
IGARSS '08 special issue of the IEEE transactions on geoscience and remote sensing (TGARS) 47 (2009), 11, S. 3857 - 3865
http://dx.doi.org/10.1109/TGRS.2009.2029340
Subject headings
[GND]: Datenfusion
[MeSH]: Neoplasms; Classification
[Free subject headings]: Decision fusion | Hyperspectral imagery | One-vs-one | ROSIS | SVM
[DDC subject group]: DDC 004 / Data processing & computer science
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DOI & citation

Please use this identifier to cite or link to this item: http://dx.doi.org/10.18725/OPARU-1735

Licciardi, Giorgio et al. (2010): Decision fusion for the classification of hyperspectral data: outcome of the 2008 GRS-S Data Fusion Contest. Open Access Repositorium der Universität Ulm und Technischen Hochschule Ulm. http://dx.doi.org/10.18725/OPARU-1735
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