Feature selection for hyperspectral data based on modified recursive support vector machines

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn 2, Issue , 2009, Pages 847-850

  Zhang, Rui ^a,b   Ma, Jianwen ^c   Chen, Xue ^a   Tong, Qingxi ^a  

^a INSTITUTE OF REMOTE SENSING APPLICATIONS   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c CENTER FOR EARTH OBSERVATION AND DIGITAL EARTH   (China)

Author keywords

Automatic modal selection (AMS); Feature selection; Hyperspectral data; Recursive support vector machines (RSVM); Support vector machines recursive feature elimination (SVM RFE)

Indexed keywords

COMPUTATIONAL EFFICIENCY; EFFICIENCY; FEATURE EXTRACTION; GEOLOGY; INFRARED SPECTROMETERS; REMOTE SENSING; THERMOGRAPHY (IMAGING); VECTORS;

AIRBORNE VISIBLE INFRARED IMAGING SPECTROMETER; AUTOMATIC MODEL SELECTION; CLASSIFICATION ACCURACY; EFFECTIVENESS AND EFFICIENCIES; HYPERSPECTRAL DATA; MODAL SELECTIONS; RECURSIVE FEATURE ELIMINATION; RECURSIVE SUPPORT VECTOR MACHINES (RSVM);

SUPPORT VECTOR MACHINES;

EID: 77951122331     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2009.5418228     Document Type: Conference Paper

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