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

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10 Seiten
10 Seiten
peer-reviewed
Veröffentlichung
2010-11-07Authors
Licciardi, Giorgio
Pacifici, Fabio
Tuia, Devis
Prasad, Saurabh
West, Terrance
Wissenschaftlicher Artikel
Faculties
Fakultät für Ingenieurwissenschaften und InformatikAbstract
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 - 3865http://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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Show full item recordDOI & 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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