Generalized relevance learning vector quantization for classification- driven feature extraction from hyperspectral data

American Society for Photogrammetry and Remote Sensing - Annual Conference of the American Society for Photogrammetry and Remote Sensing 2006: Prospecting for Geospatial Information Integration

Volumn 2, Issue , 2006, Pages 893-904

  Mendenhall, Michael J ^a   Merényi, Erzsébet ^a  

^a Rice University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL TOOL; CLASSIFICATION ACCURACY; CONVERGENCE RATES; DIVERSE MATERIALS; GENERALIZED RELEVANCE LEARNING VECTOR QUANTIZATIONS; HIGH DIMENSIONAL DATA; HIGHLY-CORRELATED; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL DATA; INPUT DIMENSIONS; KOHONEN; LEARNING VECTOR QUANTIZATION; SIGNAL CONTENT; SPECTRAL CHANNELS; SPECTRAL DOMAINS; SUPERVISED CLASSIFICATION;

DATA HANDLING; DIGITAL STORAGE; FEATURE EXTRACTION; INFORMATION RETRIEVAL; INFORMATION SCIENCE; PHOTOGRAMMETRY; REMOTE SENSING; SPECTROSCOPY; WAVELET ANALYSIS;

VECTOR QUANTIZATION;

EID: 84869041830     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

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