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  Recent trends in classification of remote sensing data: active and semisupervised machine learning paradigms

Bruzzone, L., & Persello, C. (2010). Recent trends in classification of remote sensing data: active and semisupervised machine learning paradigms. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2010) (pp. 3720-3723). Piscataway, NJ, USA: IEEE.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BF46-E Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-BF47-C
Genre: Konferenzbeitrag

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 Urheber:
Bruzzone, L, Autor
Persello, C1, Autor           
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Zusammenfassung: This paper addresses the recent trends in machine learning methods for the automatic classification of remote sensing (RS) images. In particular, we focus on two new paradigms: semisupervised and active learning. These two paradigms allow one to address classification problems in the critical conditions where the available labeled training samples are limited. These operational conditions are very usual in RS problems, due to the high cost and time associated with the collection of labeled samples. Semisupervised and active learning techniques allow one to enrich the initial training set information and to improve classification accuracy by exploiting unlabeled samples or requiring additional labeling phases from the user, respectively. The two aforementioned strategies are theoretically and experimentally analyzed considering SVM-based techniques in order to highlight advantages and disadvantages of both strategies.

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 Datum: 2010-07
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISBN: 978-1-4244-9565-8
URI: http://www.igarss10.org/
DOI: 10.1109/IGARSS.2010.5651236
BibTex Citekey: BruzzoneP2010_2
 Art des Abschluß: -

Veranstaltung

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Titel: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2010)
Veranstaltungsort: Honolulu, HI, USA
Start-/Enddatum: -

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Titel: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2010)
Genre der Quelle: Konferenzband
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Piscataway, NJ, USA : IEEE
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 3720 - 3723 Identifikator: -