Support vector selection and adaptation for remote sensing classification

IEEE Transactions on Geoscience and Remote Sensing

Volumn 49, Issue 6 PART 1, 2011, Pages 2071-2079

  Taşkin Kaya, Gülşen ^a   Ersoy, Okan K ^b   Kamaşak, Mustafa E ^a  

^a ISTANBUL TECHNICAL UNIVERSITY   (Turkey)

^b PURDUE UNIVERSITY   (United States)

Author keywords

Classification of multisource; hyperspectral and multispectral images; support vector machines (SVMs); support vector selection and adaptation (SVSA)

Indexed keywords

1-NEAREST NEIGHBOR; CLASSIFICATION METHODS; CLASSIFICATION PERFORMANCE; HYPERSPECTRAL; HYPERSPECTRAL DATA; LINEAR SVM; MULTISOURCES; NEAREST NEIGHBOR METHOD; NON-LINEARLY SEPARABLE DATA; NONLINEAR SUPPORT VECTOR MACHINES; REFERENCE VECTORS; REMOTE SENSING CLASSIFICATION; REMOTE SENSING DATA; SUPPORT VECTOR; SUPPORT VECTOR SELECTION AND ADAPTATION (SVSA); SYNTHETIC DATA; TEST DATA; TRAINING DATA;

REMOTE SENSING; SUPPORT VECTOR MACHINES; VECTORS;

CLASSIFICATION (OF INFORMATION);

EXPERIMENTAL STUDY; IMAGE CLASSIFICATION; LINEARITY; NONLINEARITY; REMOTE SENSING; SATELLITE DATA;

COLORADO; UNITED STATES;

EID: 79957656636     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2096822     Document Type: Article

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