Boosting a fast neural network for supervised land cover classification

Computers and Geosciences

Volumn 35, Issue 6, 2009, Pages 1280-1295

  Canty, Morton J ^a  

^a FORSCHUNGSZENTRUM JÜLICH   (Germany)

Author keywords

Adaptive boosting; Kalman filter; Neural networks; Satellite imagery; Supervised learning

Indexed keywords

CLASSIFICATION ACCURACIES; CLASSIFICATION PERFORMANCE; COMPUTATION TIME; ENVI/IDL; FAST NEURAL NETWORKS; GENERALIZATION ACCURACIES; KALMAN FILTER ALGORITHMS; LAND COVER CLASSIFICATIONS; MULTI-SPECTRAL IMAGERIES; MULTISPECTRAL SATELLITE DATUM; SOFTWARE IMPLEMENTATIONS; STATISTICAL HYPOTHESIS TESTS; THREE LAYERS; TRAINING TIME;

ADAPTIVE BOOSTING; CONTROL THEORY; FEEDFORWARD NEURAL NETWORKS; IMAGE ANALYSIS; IMAGE CLASSIFICATION; KALMAN FILTERS; LANDFORMS; MAXIMUM LIKELIHOOD ESTIMATION; STATISTICAL TESTS; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

SATELLITE IMAGERY;

ACCURACY ASSESSMENT; ALGORITHM; ARTIFICIAL NEURAL NETWORK; HYPOTHESIS TESTING; IMAGE ANALYSIS; KALMAN FILTER; LAND CLASSIFICATION; LAND COVER; MAXIMUM LIKELIHOOD ANALYSIS; MULTISPECTRAL IMAGE; SATELLITE DATA; SOFTWARE;

EID: 64949166678     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2008.07.004     Document Type: Article

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