Spatially adaptive classification and active learning of multispectral data with gaussian processes

ICDM Workshops 2009 - IEEE International Conference on Data Mining

Volumn , Issue , 2009, Pages 597-603

  Jun, Goo ^a   Vatsavai, Ranga Raju ^b   Ghosh, Joydeep ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b OAK RIDGE NATIONAL LABORATORY   (United States)

Author keywords

Active learning; Classification; Gaussian process; Remote sensing; Spatial statistics

Indexed keywords

ACTIVE LEARNERS; ACTIVE LEARNING; ACTIVE-LEARNING ALGORITHM; CLASSIFICATION; CLASSIFICATION ACCURACY; CLASSIFICATION ALGORITHM; GAUSSIAN PROCESSES; GEOGRAPHICAL AREA; LAND-USE AND LAND COVER CLASSIFICATIONS; MAXIMUM LIKELIHOOD CLASSIFIERS; MULTI-SPECTRAL DATA; MULTISPECTRAL REMOTE SENSING IMAGE; NUMBER OF SAMPLES; REMOTELY SENSED IMAGES; SAMPLING-BASED; SPATIAL STATISTICS; SPATIAL VARIATIONS; SPATIALLY ADAPTIVE; SPECTRAL CHARACTERISTICS; TIME AND SPACE;

CLASSIFIERS; DATA MINING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IMAGE RECONSTRUCTION; LAND USE; LEARNING SYSTEMS; MAXIMUM LIKELIHOOD; REMOTE SENSING; SPACE OPTICS; TECHNICAL PRESENTATIONS;

LEARNING ALGORITHMS;

EID: 77951146144     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDMW.2009.107     Document Type: Conference Paper

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