Comparison of artificial neural networks and support vector machine classifiers for land cover classification in Northern China using a SPOT-5 HRG image

International Journal of Remote Sensing

Volumn 33, Issue 10, 2012, Pages 3301-3320

  Song, Xianfeng ^a,b   Duan, Zheng ^a   Jiang, Xiaoguang ^b  

^a UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^b CHINESE ACADEMY OF SCIENCES   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION ALGORITHMS; CLASSIFICATION (OF INFORMATION); IMAGE CLASSIFICATION; IMAGE SEGMENTATION; LAND USE; RADIAL BASIS FUNCTION NETWORKS; REMOTE SENSING;

ADAPTIVE BACK PROPAGATION; CLASSIFICATION ACCURACY; LAND COVER CLASSIFICATION; LEVENBERG-MARQUARDT ALGORITHM; NON-PARAMETRIC CLASSIFIERS; RADIAL BASIS FUNCTION(RBF); SUPPORT VECTOR MACHINE (SVMS); SUPPORT VECTOR MACHINE CLASSIFIERS;

SUPPORT VECTOR MACHINES;

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; COMPARATIVE STUDY; LAND CLASSIFICATION; LAND COVER; REMOTE SENSING; SATELLITE IMAGERY; SPOT;

BEIJING [CHINA]; CHINA; YANQING;

EID: 84857004904     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2011.568531     Document Type: Article

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