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Volumn 1, Issue , 2005, Pages 164-167

Transductive SVMs for semisupervised classification of hyperspectral data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); DATA REDUCTION; IMAGE ANALYSIS; PROBLEM SOLVING; REMOTE SENSING;

EID: 33745699894     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2005.1526130     Document Type: Conference Paper
Times cited : (28)

References (11)
  • 2
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    • Classification of hyperspectral remotesensing images with support vector machines
    • F. Melgani and L. Bruzzone, "Classification of hyperspectral remotesensing images with support vector machines," IEEE Trans. Geosci. and Remote Sensing, vol.42, pp.1778-1790, 2004,.
    • (2004) IEEE Trans. Geosci. and Remote Sensing , vol.42 , pp. 1778-1790
    • Melgani, F.1    Bruzzone, L.2
  • 3
    • 0028499630 scopus 로고
    • He effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon
    • B.M. Shahshahani and D.A. Landgrede, "he effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes phenomenon," IEEE Trans, on Geosci. and Remote Sensing, vol. 32, no. 5, pp. 1087-1092, 1994
    • (1994) IEEE Trans, on Geosci. and Remote Sensing , vol.32 , Issue.5 , pp. 1087-1092
    • Shahshahani, B.M.1    Landgrede, D.A.2
  • 4
    • 0036564114 scopus 로고    scopus 로고
    • An adaptive method for combined covariance estimation and classification
    • May
    • Q. Jackson, and D.A. Landgrebe, "An adaptive method for combined covariance estimation and classification," IEEE Trans, on Geosci. and Remote Sensing, vol. 40, no. 5, pp. 1082-1087, May 2002.
    • (2002) IEEE Trans, on Geosci. and Remote Sensing , vol.40 , Issue.5 , pp. 1082-1087
    • Jackson, Q.1    Landgrebe, D.A.2
  • 7
    • 0038731227 scopus 로고    scopus 로고
    • Learning with progressive transductive support vector machine
    • August
    • Y. Chen, G. Wang, and S. Dong, "Learning with progressive transductive support vector machine," Pattern Recognition Letters, vol.24, Issue 12, pp. 1845-1855, August 2003.
    • (2003) Pattern Recognition Letters , vol.24 , Issue.12 , pp. 1845-1855
    • Chen, Y.1    Wang, G.2    Dong, S.3
  • 9
    • 0004322632 scopus 로고    scopus 로고
    • Sequential minimal optimization: A fast algorithm for training support vector machines
    • 21 April
    • J. Platt, "Sequential minimal optimization: a fast algorithm for training support vector machines," Technical Report MSR-TR-98-14, 21 April 1998.
    • (1998) Technical Report , vol.MSR-TR-98-14
    • Platt, J.1
  • 10
    • 0003120218 scopus 로고    scopus 로고
    • Fast training of support vector machines using sequential minimal optimization
    • B. Scholkopf, C. Surges, and A. Smola, MIT Press, December
    • J. Platt, "Fast training of support vector machines using sequential minimal optimization," in B. Scholkopf, C. Surges, and A. Smola. Advances in Kernel Methods: Support Vector Learning, MIT Press, pp. 185-208, December 1998.
    • (1998) Advances in Kernel Methods: Support Vector Learning , pp. 185-208
    • Platt, J.1
  • 11
    • 0004098720 scopus 로고    scopus 로고
    • Improvements to Plan's SMO algorithm for SVM classifier design
    • Dept of CSA, IISc, Bangalore, India
    • S. S. Keerthi, S. K. Shevade, C. Bhattacharyya, and K. R. K. Murthy, "Improvements to Plan's SMO algorithm for SVM classifier design," Technical report, Dept of CSA, IISc, Bangalore, India, 1999.
    • (1999) Technical Report
    • Keerthi, S.S.1    Shevade, S.K.2    Bhattacharyya, C.3    Murthy, K.R.K.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.