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Volumn 13, Issue 4, 2014, Pages 433-446

Optimal SVM classification for compact polarimetric data using stokes parameters

Author keywords

Compact polarimety; Decomposition; SAR; Support vector machine

Indexed keywords


EID: 84971543243     PISSN: 22142487     EISSN: 22142495     Source Type: Journal    
DOI: 10.1007/s10852-013-9244-6     Document Type: Article
Times cited : (10)

References (14)
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  • 8
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    • Nghiem, S.V.1    Yueh, S.H.2    Kwok, R.3    Li, F.K.4
  • 9
    • 33747921774 scopus 로고    scopus 로고
    • A three-component scatteringmodel for polarimetric SAR data
    • Freeman, A., Durden, S.L.: A three-component scatteringmodel for polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 36, 963-973 (1998)
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  • 10
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    • A review of polarimetry in the context of synthetic aperture radar: Concepts and information extraction
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    • Touzi, R.1    Boerner, W.-M.2    Lee, J.-S.3    Lueneburg, E.4
  • 13
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    • Support vector machine classification of land cover: Application to polarimetric SAR data
    • Fukuda, S., Hirosawa, H.: Support vector machine classification of land cover: application to polarimetric SAR data. In: Proceeding IGARSS, vol. 1, pp. 187-189 (2001)
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    • Fukuda, S.1    Hirosawa, H.2
  • 14
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    • Classification of hyperspectral remote sensing images with support vector machines
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    • Melgani, F.1    Bruzzone, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.