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Volumn , Issue , 2013, Pages 1474-1477

Semi-supervised hyperspectral band selection via sparse linear regression and hypergraph models

Author keywords

band selection; hypergraph; hyperspectral image; semi supervised learning; sparse linear regression

Indexed keywords


EID: 84894253578     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2013.6723064     Document Type: Conference Paper
Times cited : (16)

References (15)
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  • 8
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  • 9
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    • Tibshirani, R.1
  • 10
    • 84875713130 scopus 로고    scopus 로고
    • Hyperspec-tral image classification based on structured sparse lo-gistic regression and three-dimensional wavelet texture features
    • Yuntao Qian, Minchao Ye, and Jun Zhou, "Hyperspec-tral image classification based on structured sparse lo-gistic regression and three-dimensional wavelet texture features," IEEE Transactions on Geoscience and Re-mote Sensing, vol. 51, no. 4, pp. 2276-2291, 2013.
    • (2013) IEEE Transactions on Geoscience and Re-mote Sensing , vol.51 , Issue.4 , pp. 2276-2291
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  • 12
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    • Sun Han, T.1
  • 14
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    • Feature selection for classifi-cation of hyperspectral data by svm
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    • Pal, M.1    Foody, G.M.2
  • 15
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    • A joint band prioritization and band-decorrelation ap-proach to band selection for hyperspectral image classi-fication
    • C.I. Chang, Q. Du, T.L. Sun, and M.L.G. Althouse, "A joint band prioritization and band-decorrelation ap-proach to band selection for hyperspectral image classi-fication," Geoscience and Remote Sensing, IEEE Trans-Actions on, vol. 37, no. 6, pp. 2631-2641, 1999.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.