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Volumn 28, Issue 12, 2007, Pages 2821-2830

A pairwise decision tree framework for hyperspectral classification

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IMAGE CLASSIFICATION; IMAGING TECHNIQUES; INFRARED SPECTROMETERS;

EID: 34249899088     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160600954696     Document Type: Article
Times cited : (13)

References (19)
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  • 6
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    • Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries
    • Keshava, N. (2004) Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries. IEEE Transactions on Geoscience and Remote Sensing, 42, pp. 1552-1565.
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    • Keshava, N.1
  • 10
    • 84867093907 scopus 로고    scopus 로고
    • A hierarchical multiclassifier system for hyperspectral data analysis
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    • 1842431416 scopus 로고    scopus 로고
    • Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis
    • Lawrence, R., Bunn, A., Powell, S. and Zambon, M. (2004) Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis. Remote Sensing of Environment, 90, pp. 331-336.
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    • Lawrence, R.1    Bunn, A.2    Powell, S.3    Zambon, M.4
  • 16
    • 0141569007 scopus 로고    scopus 로고
    • An assessment of the effectiveness of decision tree methods for land cover classification
    • Pal, M. and Mather, P. M. (2003) An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment, 86, pp. 554-565.
    • (2003) Remote Sensing of Environment , vol.86 , pp. 554-565
    • Pal, M.1    Mather, P.M.2
  • 17
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    • A new search algorithm for feature selection in hyperspectral remote sensing images
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    • Purdue University
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    • (1998)
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.