Aggregative model-based classifier ensemble for improving land-use/cover classification of Landsat TM Images

International Journal of Remote Sensing

Volumn 35, Issue 4, 2014, Pages 1481-1495

  Li, Xuecao ^a,b   Liu, Xiaoping ^a   Yu, Le ^b  

^a SUN YAT SEN UNIVERSITY   (China)

^b TSINGHUA UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION ALGORITHMS; CHARACTER RECOGNITION; FORECASTING; IMAGE CLASSIFICATION; LAND USE; LEARNING ALGORITHMS; MAXIMUM LIKELIHOOD; NEURAL NETWORKS; SUPPORT VECTOR MACHINES;

BACK PROPAGATION NEURAL NETWORKS; CLASSIFICATION ACCURACY; CLASSIFICATION AND REGRESSION TREE; CLASSIFICATION PERFORMANCE; LANDSAT THEMATIC MAPPER IMAGES; MAXIMUM LIKELIHOOD CLASSIFIERS; MINIMUM DISTANCE CLASSIFIERS; MODEL-BASED CLASSIFIERS;

IMAGE ENHANCEMENT;

ARTIFICIAL INTELLIGENCE; ENSEMBLE FORECASTING; IMAGE CLASSIFICATION; LAND COVER; LAND USE; LANDSAT THEMATIC MAPPER; NUMERICAL MODEL; SATELLITE IMAGERY;

CHINA; DONGGUAN; GUANGDONG;

EID: 84894036072     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2013.878061     Document Type: Article

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