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Volumn 18, Issue 4, 2007, Pages 295-309

Unsupervised learning of a finite discrete mixture: Applications to texture modeling and image databases summarization

Author keywords

Cooccurrence matrix; EM; Finite mixture models; Image retrieval; Maximum likelihood; Multinomial Dirichlet; Semantic features; Vistex

Indexed keywords

IMAGE RETRIEVAL; LEARNING ALGORITHMS; MATHEMATICAL MODELS; MAXIMUM LIKELIHOOD; OPTIMIZATION; SEMANTICS;

EID: 34250816203     PISSN: 10473203     EISSN: 10959076     Source Type: Journal    
DOI: 10.1016/j.jvcir.2007.02.005     Document Type: Article
Times cited : (49)

References (45)
  • 3
    • 0033886806 scopus 로고    scopus 로고
    • Text classification from labeled and unlabeled documents using EM
    • Nigam K., McCallum A., Thrun S., and Mitchell T. Text classification from labeled and unlabeled documents using EM. Machine Learning 39 2 (2000) 103-134
    • (2000) Machine Learning , vol.39 , Issue.2 , pp. 103-134
    • Nigam, K.1    McCallum, A.2    Thrun, S.3    Mitchell, T.4
  • 4
    • 0036532779 scopus 로고    scopus 로고
    • Maximum likelihood estimation of mixture densities for binned and truncated multivariate data
    • Cadez I.V., McLachlan J.G., and McLarn C.E. Maximum likelihood estimation of mixture densities for binned and truncated multivariate data. Machine Learning 47 (2002) 7-43
    • (2002) Machine Learning , vol.47 , pp. 7-43
    • Cadez, I.V.1    McLachlan, J.G.2    McLarn, C.E.3
  • 5
    • 0027453616 scopus 로고
    • Model-based Gaussian and non-Gaussian clustering
    • Raftery A.E., and Banfield J.D. Model-based Gaussian and non-Gaussian clustering. Biometrics 49 (1993) 803-821
    • (1993) Biometrics , vol.49 , pp. 803-821
    • Raftery, A.E.1    Banfield, J.D.2
  • 6
    • 7444239786 scopus 로고    scopus 로고
    • Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application
    • Bouguila N., Ziou D., and Vaillancourt J. Unsupervised learning of a finite mixture model based on the Dirichlet distribution and its application. IEEE Transactions on Image Processing 13 11 (2004) 1533-1543
    • (2004) IEEE Transactions on Image Processing , vol.13 , Issue.11 , pp. 1533-1543
    • Bouguila, N.1    Ziou, D.2    Vaillancourt, J.3
  • 8
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic latent semantic analysis
    • Hofman T. Unsupervised learning by probabilistic latent semantic analysis. Machine Learning 42 1 (2001) 177-196
    • (2001) Machine Learning , vol.42 , Issue.1 , pp. 177-196
    • Hofman, T.1
  • 10
    • 34250898784 scopus 로고    scopus 로고
    • N. Bouguila, D. Ziou, Apprentissage non Supervisé d'un Mélange Discret et Fini Basé sur la Distribution de Dirichlet Multinomiale: Application à la Modélisation de la Texture, in: Proc. Of 14ème Congrès Francophone AFRIF-AFIA de Reconnaissance des Formes et Intelligence Artificielle (RFIA2004), 2004, pp. 469-479.
  • 11
    • 34250872998 scopus 로고    scopus 로고
    • J.D.M. Rennie, L. Shih, J. Teevan, D.R. Karger, Parametric mixture models for multi-labeled text, in: Proc. Neural Information Processing Systems (NIPS2002), 2002, pp. 721-728.
  • 12
    • 1942484786 scopus 로고    scopus 로고
    • J.D.M. Rennie, L. Shih, J. Teevan, D.R. Karger, Tackling the poor assumptions of naive Bayes text classifiers, in: Proc. International Conference on Machine Learning (ICML2003), 2003, pp. 616-623.
  • 13
    • 84957069091 scopus 로고    scopus 로고
    • D. Lewis, Naive (Bayes) at forty: The independence assumption in information retrieval, in: Proc. European Conference on Machine Learning (ECML1998), 1998, pp. 4-15.
  • 17
    • 0030092468 scopus 로고    scopus 로고
    • Distribution of content words and phrases in text and language modelling
    • Katz S.M. Distribution of content words and phrases in text and language modelling. Natural Language Engineering 2 (1996) 15-59
    • (1996) Natural Language Engineering , vol.2 , pp. 15-59
    • Katz, S.M.1
  • 18
    • 1542754043 scopus 로고    scopus 로고
    • J. Teevan, D.R. Karger, Empirical development of an exponential probabilistic model for text retrieval: Using textual analysis to build a better model, in: Proc. 26th Annual International ACMSIGIR Conference on Research and Development in Informaion Retrieval, 2003, p. 1825.
  • 19
    • 0345306663 scopus 로고    scopus 로고
    • Implications of the Dirichlet assumption for discretization of continuous variables in naive Bayesian classifier
    • Hsu C.N., Huang H.J., and Wong T.T. Implications of the Dirichlet assumption for discretization of continuous variables in naive Bayesian classifier. Machine Learning 53 (2003) 235-623
    • (2003) Machine Learning , vol.53 , pp. 235-623
    • Hsu, C.N.1    Huang, H.J.2    Wong, T.T.3
  • 21
    • 0002567040 scopus 로고
    • On the compound multinomial distribution, the multivariate β-distribution, and correlations among proportions
    • Mosimann J.E. On the compound multinomial distribution, the multivariate β-distribution, and correlations among proportions. Biometrika 49 1 and 2 (1962) 65-82
    • (1962) Biometrika , vol.49 , Issue.1-2 , pp. 65-82
    • Mosimann, J.E.1
  • 22
    • 0002617436 scopus 로고
    • Ferguson distributions via polya urn schemes
    • Blackwll D., and MacQueen J.B. Ferguson distributions via polya urn schemes. The Annals of Statistics 1 (1973) 353-355
    • (1973) The Annals of Statistics , vol.1 , pp. 353-355
    • Blackwll, D.1    MacQueen, J.B.2
  • 23
    • 0015824327 scopus 로고
    • Maximum likelihood estimation for the beta-binomial distribution and an application to the household distribution of the total number of cases of a disease
    • Griffiths D.A. Maximum likelihood estimation for the beta-binomial distribution and an application to the household distribution of the total number of cases of a disease. Biometrics 29 4 (1973) 637-648
    • (1973) Biometrics , vol.29 , Issue.4 , pp. 637-648
    • Griffiths, D.A.1
  • 24
    • 34250818918 scopus 로고    scopus 로고
    • S.A. Lowe, The beta-binomial mixture model and its application to TDT tracking and detection, in: Proc. of the DARPA Broadcast News Workshop, 1999.
  • 25
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and EM algorithm
    • Redner R.A., and Walker H.F. Mixture densities, maximum likelihood and EM algorithm. SIAM Review 26 2 (1984) 195-239
    • (1984) SIAM Review , vol.26 , Issue.2 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 26
    • 0016355478 scopus 로고
    • New look at the statistical model identification
    • Akaike H.A. New look at the statistical model identification. IEEE Transaction on Automatic Control 19 6 (1994) 716-723
    • (1994) IEEE Transaction on Automatic Control , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.A.1
  • 27
    • 0041728999 scopus 로고
    • Modeling by shortest data description
    • Rissanen J. Modeling by shortest data description. Automatica 49 1 and 2 (1978) 65-82
    • (1978) Automatica , vol.49 , Issue.1-2 , pp. 65-82
    • Rissanen, J.1
  • 28
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • Schwarz G. Estimating the dimension of a model. The Annals of Statistics 6 2 (1978) 361-464
    • (1978) The Annals of Statistics , vol.6 , Issue.2 , pp. 361-464
    • Schwarz, G.1
  • 30
    • 10044252969 scopus 로고    scopus 로고
    • A.A. Salah, E. Alpaydin, Incremental mixtures of factor analysers, in: International Conference on Pattern Recognition (ICPR'04), 2004, pp. 276-279.
  • 33
    • 85005423785 scopus 로고
    • Estimation of parameters in the beta distribution
    • Fielitz B.D., and Myers B.L. Estimation of parameters in the beta distribution. Decision Sciences 6 (1975) 1-13
    • (1975) Decision Sciences , vol.6 , pp. 1-13
    • Fielitz, B.D.1    Myers, B.L.2
  • 34
    • 34250864075 scopus 로고    scopus 로고
    • M. Tuceryan, A.K. Jain, Texture analysis, in: The Handbook of Pattern Recognition and Computer Vision, 1998, pp. 207-248.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.