Hyperspectral Image Classification with Limited Labeled Training Samples Using Enhanced Ensemble Learning and Conditional Random Fields

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 8, Issue 6, 2015, Pages 2427-2438

  Li, Fan ^a   Xu, Linlin ^a   Siva, Parthipan ^a   Wong, Alexander ^a   Clausi, David A ^a  

^a UNIVERSITY OF WATERLOO   (Canada)

Author keywords

Ada Boost; conditional random fields (Crfs); hyperspectral data classification; rotation forests (Rof)

Indexed keywords

ADAPTIVE BOOSTING; CLASSIFICATION (OF INFORMATION); FORESTRY; IMAGE SEGMENTATION; RANDOM PROCESSES; REMOTE SENSING; SAMPLING; SPECTROSCOPY;

CLASSIFICATION ACCURACY; CONDITIONAL RANDOM FIELD; CONDITIONAL RANDOM FIELDS(CRFS); GENERALIZATION CAPABILITY; HYPER-SPECTRAL IMAGERIES; HYPERSPECTRAL DATA CLASSIFICATION; HYPERSPECTRAL IMAGE CLASSIFICATION; ROTATION FORESTS;

IMAGE CLASSIFICATION;

ALGORITHM; ENSEMBLE FORECASTING; FOREST; IMAGE CLASSIFICATION; REMOTE SENSING; SPECTRAL ANALYSIS; TRAINING; VARIANCE ANALYSIS;

ALGORITHMS; CLASSIFICATION; EDUCATION; PROBLEM SOLVING;

EID: 85027945747     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2015.2414816     Document Type: Article

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