Sensitivity of hyperspectral classification algorithms to training sample size

WHISPERS '09 - 1st Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

Volumn , Issue , 2009, Pages

  Lee, Matthew A ^a   Prasad, Saurabh ^b   Bruce, Lori Mann ^a   West, Terrance R ^a   Reynolds, Daniel ^b   Irby, Trent ^b   Kalluri, Hemanth ^a  

^a MISSISSIPPI STATE UNIVERSITY   (United States)

^b MISSISSIPPI STATE UNIVERSITY   (United States)

Author keywords

Discrete Wavelet Transforms; Hyperspectral; Information fusion; Pattern recognition

Indexed keywords

CLASSIFICATION APPROACH; CLASSIFICATION SYSTEM; CONVENTIONAL ALGORITHMS; DISCRETE WAVELETS; EXPERIMENTAL ANALYSIS; FUSION PATTERN; HIGH DIMENSIONALITY; HYPER-SPECTRAL CLASSIFICATION; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGERS; HYPERSPECTRAL IMAGERY; HYPERSPECTRAL INFORMATION; LIMITED TRAINING DATA; MULTI-CLASSIFIER; SMALL SAMPLE SIZE PROBLEMS; SPECTRAL BAND; TRAINING DATA; TRAINING SAMPLE;

ALGORITHMS; CLASSIFIERS; FACE RECOGNITION; INFORMATION FUSION; LEARNING SYSTEMS; MATHEMATICAL TRANSFORMATIONS; REMOTE SENSING; SENSITIVITY ANALYSIS; SIGNAL PROCESSING;

DISCRETE WAVELET TRANSFORMS;

EID: 72049110821     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WHISPERS.2009.5288983     Document Type: Conference Paper

References (7)

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