메뉴 건너뛰기




Volumn , Issue , 2004, Pages 320-326

A kernel-based supervised classifier for the analysis of hyperspectral data

Author keywords

Bayes classifier; kernel machines

Indexed keywords

COVARIANCE MATRIX; LINEAR TRANSFORMATIONS; MATHEMATICAL TRANSFORMATIONS; NORMAL DISTRIBUTION; REMOTE SENSING;

EID: 84945265247     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WARSD.2003.1295211     Document Type: Conference Paper
Times cited : (1)

References (21)
  • 1
    • 0033886806 scopus 로고    scopus 로고
    • Text Classification from Labeled and Unlabeled Documents using em
    • K. Nigam, A. McCallum, S. Thrun, and T. Mitchell,"Text Classification from Labeled and Unlabeled Documents using EM," Machine Learning, vol. 39 (2/3), pp. 103-134, 2000.
    • (2000) Machine Learning , vol.39 , Issue.2-3 , pp. 103-134
    • Nigam, K.1    McCallum, A.2    Thrun, S.3    Mitchell, T.4
  • 2
    • 0028499630 scopus 로고
    • The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes Phenomenon
    • B.M. Shahshahani and D.A. Landgrebe, "The effect of unlabeled samples in reducing the small sample size problem and mitigating the Hughes Phenomenon," IEEE Trans. Geoscience and Remote Sensing, vol. 32, no. 5, pp. 1087-1095, 1994.
    • (1994) IEEE Trans. Geoscience and Remote Sensing , vol.32 , Issue.5 , pp. 1087-1095
    • Shahshahani, B.M.1    Landgrebe, D.A.2
  • 3
    • 0036991339 scopus 로고    scopus 로고
    • A model based mixture classification approach in hyperspectral data analysis
    • M. M. Dundar and D. Landgrebe, "A model based mixture classification approach in hyperspectral data analysis," IEEE Trans. Geoscience and Remote Sensing, vol. 40, no. 12, 2002.
    • (2002) IEEE Trans. Geoscience and Remote Sensing , vol.40 , Issue.12
    • Dundar, M.M.1    Landgrebe, D.2
  • 8
    • 27144489164 scopus 로고    scopus 로고
    • A Tutorial on Support vector machines for pattern recognition
    • C. J. C. Burges. "A Tutorial on Support Vector Machines for Pattern Recognition," Data Mining and Knowledge Discovery, vol. 2, pp. 955-974, 1998.
    • (1998) Data Mining and Knowledge Discovery , vol.2 , pp. 955-974
    • Burges, C.J.C.1
  • 11
    • 0032594954 scopus 로고    scopus 로고
    • Input Space vs. Feature space in kernel-based methods
    • B. Scholkopf et al., "Input Space vs. Feature Space in Kernel-Based Methods," IEEE Trans. on Neural Networks, vol. 10, no. 5, pp. 1000-1017, 1999.
    • (1999) IEEE Trans. on Neural Networks , vol.10 , Issue.5 , pp. 1000-1017
    • Scholkopf, B.1
  • 14
    • 0035172225 scopus 로고    scopus 로고
    • Support vector machines for broad area feature extraction in remotely sensed images
    • S. Perkins et al., Support Vector Machines for Broad Area Feature Extraction in Remotely Sensed Images. Proc. SPIE 4381, 2001.
    • (2001) Proc. SPIE , pp. 4381
    • Perkins, S.1
  • 15
    • 0032636659 scopus 로고    scopus 로고
    • Support Vector machines for hyperspectral remote sensing classification
    • A. J. Gualtieri and R.F. Cromp, "Support Vector Machines for Hyperspectral Remote Sensing Classification," Proc. SPIE 3584, 221-232, 1999.
    • (1999) Proc. SPIE , vol.3584 , pp. 221-232
    • Gualtieri, A.J.1    Cromp, R.F.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.