An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery

Zhang, Liangpei; Huang, Xin

doi:10.1109/TGRS.2012.2202912

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An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery

Author(s): Xin Huang , Liangpei Zhang

Publication date (Print): January 2013

Journal: IEEE Transactions on Geoscience and Remote Sensing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

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On the mean accuracy of statistical pattern recognizers

G. Hughes (1968)

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The Divergence and Bhattacharyya Distance Measures in Signal Selection

T Kailath (1967)

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Classification of hyperspectral data from urban areas based on extended morphological profiles

J.A. Benediktsson, J.A. Palmason, J.R. Sveinsson (2005)

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Journal

Title: IEEE Transactions on Geoscience and Remote Sensing

Abbreviated Title: IEEE Trans. Geosci. Remote Sensing

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

ISSN (Print): 0196-2892

ISSN (Electronic): 1558-0644

Publication date Created: January 2013

Publication date (Print): January 2013

Volume: 51

Issue: 1

Pages: 257-272

Article

DOI: 10.1109/TGRS.2012.2202912

SO-VID: dfc7705f-d571-4d6e-98b7-d39f16e79ad5

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An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery

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Music and Mental Imagery

Most cited references 46

On the mean accuracy of statistical pattern recognizers

The Divergence and Bhattacharyya Distance Measures in Signal Selection

Classification of hyperspectral data from urban areas based on extended morphological profiles

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