메뉴 건너뛰기




Volumn 7594 LNCS, Issue , 2012, Pages 465-474

Stability of dimensionality reduction methods applied on artificial hyperspectral images

Author keywords

Dimensionality reduction; hyperspectral data; manifold learning; stability spectral criteria

Indexed keywords

COMPUTER VISION; SPECTROSCOPY; STABILITY CRITERIA;

EID: 84868034811     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33564-8_56     Document Type: Conference Paper
Times cited : (10)

References (28)
  • 3
    • 84859350065 scopus 로고    scopus 로고
    • Dimensionality reduction via compressive sensing
    • Gao, Shi, Q., Caetano, T.S.: Dimensionality reduction via compressive sensing. Pattern Recognition Letters 33(9), 1163-1170 (2012)
    • (2012) Pattern Recognition Letters , vol.33 , Issue.9 , pp. 1163-1170
    • Gao Shi, Q.1    Caetano, T.S.2
  • 6
    • 58249094366 scopus 로고    scopus 로고
    • Weighted locally linear embedding for dimension reduction
    • Pan, Y., Ge, S.S., Mamun, A.A.: Weighted locally linear embedding for dimension reduction. Pattern Recognition 42(5), 798-811 (2009)
    • (2009) Pattern Recognition , vol.42 , Issue.5 , pp. 798-811
    • Pan, Y.1    Ge, S.S.2    Mamun, A.A.3
  • 8
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Scholkopf, B., Smola, A., Muller, K.R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10, 1299-1319 (1998)
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Scholkopf, B.1    Smola, A.2    Muller, K.R.3
  • 9
    • 67349170432 scopus 로고    scopus 로고
    • Stable local dimensionality reduction approaches
    • Jiao, Y., Wu, Y., Hou, C., Zhang, C.: Stable local dimensionality reduction approaches. Pattern Recognition 42(9), 2054-2066 (2006)
    • (2006) Pattern Recognition , vol.42 , Issue.9 , pp. 2054-2066
    • Jiao, Y.1    Wu, Y.2    Hou, C.3    Zhang, C.4
  • 10
    • 77955742943 scopus 로고    scopus 로고
    • Comparative study of dimensionality reduction techniques for data visualization
    • Tsai, F.S.: Comparative Study of Dimensionality Reduction Techniques for Data Visualization. Journal of Artificial Intelligence 3(3), 119-134 (2010)
    • (2010) Journal of Artificial Intelligence , vol.3 , Issue.3 , pp. 119-134
    • Tsai, F.S.1
  • 11
    • 28444473249 scopus 로고    scopus 로고
    • Supervised nonlinear dimensionality reduction for visualization and classification
    • Geng, X., Zhan, D.C., Zhou, Z.H.: Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Trans. Syst. Man Cybernetics Part B 35, 1098-1107 (2005)
    • (2005) IEEE Trans. Syst. Man Cybernetics Part B , vol.35 , pp. 1098-1107
    • Geng, X.1    Zhan, D.C.2    Zhou, Z.H.3
  • 13
    • 58149421595 scopus 로고
    • Analysis of a complex of statistical variables into principal components
    • Hotelling, H.: Analysis of a complex of statistical variables into principal components. Journal of Educational Psychology 24, 417-441 (1933)
    • (1933) Journal of Educational Psychology , vol.24 , pp. 417-441
    • Hotelling, H.1
  • 14
    • 0000325341 scopus 로고
    • On lines and planes of closest fit to systems of points in space
    • Pearson, K.: On lines and planes of closest fit to systems of points in space. Philiosophical Magazine 2, 559-572 (1901)
    • (1901) Philiosophical Magazine , vol.2 , pp. 559-572
    • Pearson, K.1
  • 17
    • 14544307975 scopus 로고    scopus 로고
    • Principal manifolds and nonlinear dimensionality reduction via local tangent space alignment
    • Zhang, Z., Zha, H.: Principal manifolds and nonlinear dimensionality reduction via local tangent space alignment. SIAM Journal of Scientific Computing 26(1), 313-338 (2004)
    • (2004) SIAM Journal of Scientific Computing , vol.26 , Issue.1 , pp. 313-338
    • Zhang, Z.1    Zha, H.2
  • 21
    • 0037948870 scopus 로고    scopus 로고
    • Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
    • Donoho, D.L., Grimes, C.: Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data. PNAS 100, 5591-5596 (2003)
    • (2003) PNAS , vol.100 , pp. 5591-5596
    • Donoho, D.L.1    Grimes, C.2
  • 22
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 15, 1373-1396 (2003)
    • (2003) Neural Comput. , vol.15 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 25
    • 0027829865 scopus 로고
    • A survey of quality measures for gray scale image compression
    • AIAA, October
    • Eskicioglu, M., Fisher, P.S.: A survey of quality measures for gray scale image compression. In: 9th Computing in Aerospace Conference, pp. 49-61. AIAA (October 1993)
    • (1993) 9th Computing in Aerospace Conference , pp. 49-61
    • Eskicioglu, M.1    Fisher, P.S.2
  • 27
    • 14544297033 scopus 로고    scopus 로고
    • KPCA plus LDA: A complete kernel fisher discriminant framework for feature extraction and recognition
    • Yang, J., Frangi, A.F., Yang, J., Jin, Z.: KPCA Plus LDA: A Complete Kernel Fisher Discriminant Framework for Feature Extraction and Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 27(2), 230-244 (2005)
    • (2005) IEEE Trans. Pattern Anal. Mach. Intell. , vol.27 , Issue.2 , pp. 230-244
    • Yang, J.1    Frangi, A.F.2    Yang, J.3    Jin, Z.4
  • 28
    • 33749546693 scopus 로고    scopus 로고
    • Non-linear dimensionality reduction by locally linear isomaps
    • Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds.). Springer, Heidelberg, ICONIP 2004
    • Saxena, A., Gupta, A., Mukerjee, A.: Non-linear Dimensionality Reduction by Locally Linear Isomaps. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds.) ICONIP 2004. LNCS, vol. 3316, pp. 1038-1043. Springer, Heidelberg (2004)
    • (2004) LNCS , vol.3316 , pp. 1038-1043
    • Saxena, A.1    Gupta, A.2    Mukerjee, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.