Active learning of very-high resolution optical imagerywith svm: entropy vs margin sampling

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 4, Issue 1, 2008, Pages 73-76

  Tuia, D ^a   Ratle, F ^a   Pacifici, F ^b   Pozdnoukhov, A ^a   Kanevski, M ^a   Del Frate, F ^b   Solimini, D ^b   Emery, W J ^c  

^a UNIVERSITY OF LAUSANNE   (Switzerland)

^b UNIVERSITY OF ROME TOR VERGATA   (Italy)

^c University of Colorado at Boulder   (United States)

Author keywords

Active learning; entropy; margin sampling; query learning; support vector machines; VHR imagery

Indexed keywords

CLASSIFICATION (OF INFORMATION); ENTROPY; GEOLOGY; ITERATIVE METHODS; MAXIMUM ENTROPY METHODS; PIXELS; REMOTE SENSING; SUPPORT VECTOR MACHINES;

ACTIVE LEARNING; ACTIVE LEARNING METHODS; ENSEMBLE OF CLASSIFIERS; QUERY LEARNING; REMOTE SENSING IMAGE CLASSIFICATION; STATE OF THE ART; VERY HIGH RESOLUTION; VHR IMAGERY;

LEARNING SYSTEMS;

EID: 67649825770     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2008.4779659     Document Type: Conference Paper

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