14.2.7 Mixture Models, Mixed Pixels

Chapter Contents (Back)
Mixed Pixels. Mixture Models. 9905

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Kitamoto, A.[Asanbou], Takagi, M.[Mikio],
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Earlier:
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Cootes, T.F., Taylor, C.J.,
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Boshra, M.[Michael], Zhang, H.[Hong],
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Aguiar, A.P.D., Shimabukuro, Y.E., Mascarenhas, N.D.A.,
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Carreira-Perpińán, M.Á.[Miguel Á.], Williams, C.K.I.[Christopher K.I.],
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Carreira-Perpinan, M.A.[Miguel A.],
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Carreira-Perpinan, M.A.[Miguel A.],
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Chang, C.I., Ji, B.,
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Chang, C.I.[Chein-I], Chiang, S.S.[Shao-Shan], Smith, J.A., Ginsberg, I.W.,
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Simon, C., Loubaton, P., Jutten, C.,
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Dahmen, J.[Jörg], Keysers, D.[Daniel], Ney, H.[Hermann], Güld, M.O.[Mark Oliver],
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Keysers, D.[Daniel], Macherey, W.[Wolfgang], Ney, H.[Hermann], Dahmen, J.[Jorg],
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Rand, R.S., Keenan, D.M.,
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Dattatreya, G.R.,
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Discrete features; Finite mixture models; Multinomial; Dirichlet; Generalized Dirichlet; Leave-one-out likelihood; SVM; Generative/discriminative; Scene classification; Visual words BibRef

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Haertel, V.F., Shimabukuro, Y.E.,
Spectral linear mixing model in low spatial resolution image data,
GeoRS(43), No. 11, November 2005, pp. 2555-2562.
IEEE DOI Link 0512
BibRef

Shi, Z.W.[Zhen-Wei], Tang, H.W.[Huan-Wen], Tang, Y.Y.[Yi-Yuan],
Blind source separation of more sources than mixtures using sparse mixture models,
PRL(26), No. 16, December 2005, pp. 2491-2499.
WWW Version. 0512
BibRef

Shi, Z.W.[Zhen-Wei], Zhang, C.S.[Chang-Shui],
Fast nonlinear autocorrelation algorithm for source separation,
PR(42), No. 9, September 2009, pp. 1732-1741.
Elsevier DOI Link
WWW Version. 0905
Blind source separation (BSS); Independent component analysis (ICA); Linear autocorrelation; Nonlinear autocorrelation BibRef

Permuter, H.H.[Haim H.], Francos, J.M.[Joseph M.], Jermyn, I.H.[Ian H.],
A study of Gaussian mixture models of color and texture features for image classification and segmentation,
PR(39), No. 4, April 2006, pp. 695-706.
WWW Version. 0604
Image classification; Texture; Color; Gaussian mixture models; Expectation maximization; k-means; Background model; Decision fusion; Aerial images BibRef

Lin, T.I.[Tsung I.], Lee, J.C.[Jack C.], Ho, H.J.[Hsiu J.],
On fast supervised learning for normal mixture models with missing information,
PR(39), No. 6, June 2006, pp. 1177-1187.
WWW Version. Bayesian classifier; Data augmentation; EM algorithm; Incomplete features; Rao-Blackwellization 0604
BibRef

Paalanen, P.[Pekka], Kamarainen, J.K.[Joni-Kristian], Ilonen, J.[Jarmo], Kälviäinen, H.[Heikki],
Feature representation and discrimination based on Gaussian mixture model probability densities: Practices and algorithms,
PR(39), No. 7, July 2006, pp. 1346-1358.
WWW Version. 0606
Gaussian mixture model; EM; Classifier; Confidence; Highest density region BibRef

Zhou, X., Wang, X.,
Optimisation of Gaussian mixture model for satellite image classification,
VISP(153), No. 3, June 2006, pp. 349-356.
WWW Version. 0608
BibRef

Brandt, S.S.[Sami S.],
Maximum Likelihood Robust Regression by Mixture Models,
JMIV(25), No. 1, July 2006, pp. 25-48.
Springer DOI Link 0610
BibRef

Pyun, K.[Kyungsuk], Lim, J., Won, C.S.[Chee Sun], Cray, R.M.,
Image Segmentation Using Hidden Markov Gauss Mixture Models,
IP(16), No. 7, July 2007, pp. 1902-1911.
IEEE DOI Link 0707
BibRef
Earlier: A1, A3, A2, A4:
Robust image classification based on a non-causal hidden markov gauss mixture model,
ICIP02(III: 785-788).
IEEE Abstract. 0210
BibRef

Lim, J., Pyun, K.,
Cost-Effective Hidden Markov Model-Based Image Segmentation,
SPLetters(16), No. 3, March 2009, pp. 172-175.
IEEE DOI Link 0903
BibRef

Tawfick, M.M.[Mohamad M.], Abbas, H.M.[Hazem M.], Shahein, H.I.[Hussein I.],
An integer-coded evolutionary approach for mixture maximum likelihood clustering,
PRL(29), No. 4, 1 March 2008, pp. 515-524.
WWW Version. 0711
Clustering; Mixture maximum likelihood; Evolutionary algorithms; Genetic algorithms BibRef

Goldberger, J.[Jacob], Greenspan, H.K.[Hayit K.], Dreyfuss, J.[Jeremie],
Simplifying Mixture Models Using the Unscented Transform,
PAMI(30), No. 8, August 2008, pp. 1496-1502.
IEEE DOI Link 0806
BibRef

Rotem, O.[Omer], Greenspan, H.K.[Hayit K.], Goldberger, J.[Jacob],
Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework,
CVPR07(1-8).
IEEE DOI Link 0706
BibRef

Reddy, C.K.[Chandan K.], Chiang, H.D.[Hsiao-Dong], Rajaratnam, B.[Bala],
TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models,
PAMI(30), No. 7, July 2008, pp. 1146-1157.
IEEE DOI Link 0806
BibRef

Omachi, S.[Shinichiro], Omachi, M.[Masako], Aso, H.[Hirotomo],
An Approximation Method of the Quadratic Discriminant Function and Its Application to Estimation of High-Dimensional Distribution,
IEICE(E90-D), No. 8, August 2007, pp. 1160-1167.
WWW Version. 0708
BibRef

Omachi, S., Sun, F., Aso, H.,
A Discriminant Function for Noisy Pattern Recognition,
SCIA99(Statistical Methods). BibRef 9900

Sun, F., Omachi, S., Aso, H.,
An Algorithm for Estimating Mixture Distribution of High Dimensional Vectors and its Application to Character Recognition,
SCIA99(Statistical Methods). BibRef 9900

Liang, Z., Wang, S.,
An EM Approach to MAP Solution of Segmenting Tissue Mixtures: A Numerical Analysis,
MedImg(28), No. 2, February 2009, pp. 297-310.
IEEE DOI Link 0902
BibRef
And: Erratum: MedImg(28), No. 4, April 2009, pp. 631-631.
IEEE DOI Link 0904
Mixed voxels. BibRef

Liu, L.F.[Li-Fan], Wang, B.[Bin], Zhang, L.M.[Li-Ming],
Decomposition of mixed pixels based on bayesian self-organizing map and Gaussian mixture model,
PRL(30), No. 9, 1 July 2009, pp. 820-826.
Elsevier DOI Link
WWW Version. 0905
Decomposition of mixed pixels; Bayesian self-organization map (BSOM); Gaussian mixture model (GMM); Multispectral/hyperspectral data BibRef

Sabuncu, M.R., Balci, S.K., Shenton, M.E., Golland, P.,
Image-Driven Population Analysis Through Mixture Modeling,
MedImg(28), No. 9, September 2009, pp. 1473-1487.
IEEE DOI Link 0909
BibRef

Yamada, M.[Makoto], Sugiyama, M.[Masashi],
Direct Importance Estimation with Gaussian Mixture Models,
IEICE(E92-D), No. 10, October 2009, pp. 2159-2162.
WWW Version. 0910
BibRef

Bruneau, P.[Pierrick], Gelgon, M.[Marc], Picarougne, F.[Fabien],
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach,
PR(43), No. 3, March 2010, pp. 850-858.
Elsevier DOI Link
WWW Version. 1001
BibRef
Earlier:
Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach,
ICPR08(1-4).
IEEE DOI Link 0812
Mixture models; Bayesian estimation; Model aggregation BibRef

Filippone, M.[Maurizio], Sanguinetti, G.[Guido],
Information theoretic novelty detection,
PR(43), No. 3, March 2010, pp. 805-814.
Elsevier DOI Link
WWW Version. 1001
Novelty detection; Information theory; Mixture of Gaussians; Density estimation BibRef

Kristan, M.[Matej], Skocaj, D.[Danijel], Leonardis, A.[Ales],
Online kernel density estimation for interactive learning,
IVC(28), No. 7, July 2010, pp. 1106-1116.
Elsevier DOI Link
WWW Version. 1006
Online learning; Kernel density estimation; Mixture models; Unlearning; Compression; Hellinger distance; Unscented transform BibRef

Kristan, M.[Matej], Leonardis, A.[Ales], Skocaj, D.[Danijel],
Multivariate online kernel density estimation with Gaussian kernels,
PR(44), No. 10-11, October-November 2011, pp. 2630-2642.
Elsevier DOI Link
WWW Version. 1101
BibRef
Earlier: A1, A2, Only:
Online Discriminative Kernel Density Estimation,
ICPR10(581-584).
IEEE DOI Link 1008
Online models; Probability density estimation; Kernel density estimation; Gaussian mixture models BibRef

Vogler, N.[Nadine], Bocklitz, T.[Thomas], Mariani, M.[Melissa], Deckert, V.[Volker], Markova, A.[Aneta], Schelkens, P.[Peter], Rösch, P.[Petra], Akimov, D.[Denis], Dietzek, B.[Benjamin], Popp, J.[Jürgen],
Separation of CARS image contributions with a Gaussian mixture model,
JOSA-A(27), No. 6, June 2010, pp. 1361-1371.
WWW Version. 1006
BibRef

Mei, S., He, M., Wang, Z., Feng, D.,
Spatial Purity Based Endmember Extraction for Spectral Mixture Analysis,
GeoRS(48), No. 9, September 2010, pp. 3434-3445.
IEEE DOI Link 1008
Mixed pixel problem. Exploit spatial context. BibRef

Hidot, S.[Sullivan], Saint-Jean, C.[Christophe],
An Expectation-Maximization algorithm for the Wishart mixture model: Application to movement clustering,
PRL(31), No. 14, 15 October 2010, pp. 2318-2324.
Elsevier DOI Link
WWW Version. 1003
Wishart mixture model; EM algorithm; Clustering; Second-order cross moments; Movement recognition BibRef

Yang, F.[Fan], Matsushita, B.[Bunkei], Fukushima, T.[Takehiko],
A pre-screened and normalized multiple endmember spectral mixture analysis for mapping impervious surface area in Lake Kasumigaura Basin, Japan,
PandRS(65), No. 5, September 2010, pp. 479-490.
Elsevier DOI Link
WWW Version. 1003
Impervious surface area; Spectral mixture analysis; Endmember selection; Lake Kasumigaura Basin BibRef

Rabbani, H., Gazor, S.,
Image denoising employing local mixture models in sparse domains,
IET-IPR(4), No. 5, October 2010, pp. 413-428.
WWW Version. 1011
BibRef

Chang, C.I., Xiong, W., Liu, W., Chang, M.L., Wu, C.C., Chen, C.C.C.,
Linear Spectral Mixture Analysis Based Approaches to Estimation of Virtual Dimensionality in Hyperspectral Imagery,
GeoRS(48), No. 11, November 2010, pp. 3960-3979.
IEEE DOI Link 1011
BibRef

Sun, J.Y.[Jian-Yong], Kaban, A.[Ata], Garibaldi, J.M.[Jonathan M.],
Robust mixture clustering using Pearson type VII distribution,
PRL(31), No. 16, December 2010, pp. 2447-2454.
Elsevier DOI Link
WWW Version. 1011
Robust mixture modeling; Pearson type VII distribution; Outlier detection; Robust learning BibRef

Ulker, Y.[Yener], Gunsel, B.[Bilge], Cemgil, A.T.[Ali Taylan],
Annealed SMC Samplers for Nonparametric Bayesian Mixture Models,
SPLetters(18), No. 1, January 2011, pp. 3-6.
IEEE DOI Link 1011
BibRef
Earlier:
Annealed SMC Samplers for Dirichlet Process Mixture Models,
ICPR10(2808-2811).
IEEE DOI Link 1008
BibRef

Peng, L.Q.[Liu-Qing], Zhang, J.Y.[Jun-Ying],
An entropy weighting mixture model for subspace clustering of high-dimensional data,
PRL(32), No. 8, 1 June 2011, pp. 1154-1161.
Elsevier DOI Link
WWW Version. 1101
Subspace clustering; High-dimensional data; Gaussian mixture models; Local feature relevance; Shape volume BibRef

Xie, C.H.[Cong-Hua], Song, Y.Q.[Yu-Qing], Chen, J.M.[Jian-Mei],
Fast medical image mixture density clustering segmentation using stratification sampling and kernel density estimation,
SIViP(5), No. 2, June 2011, pp. 257-267.
WWW Version. 1101
BibRef

Ma, Z.Y.[Zhan-Yu], Leijon, A.[Arne],
Bayesian Estimation of Beta Mixture Models with Variational Inference,
PAMI(33), No. 11, November 2011, pp. 2160-2173.
IEEE DOI Link 1110
BibRef
Earlier:
Beta mixture models and the application to image classification,
ICIP09(2045-2048).
IEEE DOI Link 0911
BibRef

Chatzis, S.P.[Sotirios P.], Tsechpenakis, G.[Gavriil],
A possibilistic clustering approach toward generative mixture models,
PR(45), No. 5, May 2012, pp. 1819-1825.
Elsevier DOI Link
WWW Version. 1201
Possibilistic clustering; Finite mixture models BibRef

Nguyen, T.M.[Thanh Minh], Wu, Q.M.J.,
Robust Student's-t Mixture Model With Spatial Constraints and Its Application in Medical Image Segmentation,
MedImg(31), No. 1, January 2012, pp. 103-116.
IEEE DOI Link 1201
BibRef

Raitoharju, M., Ali-Loytty, S.,
An Adaptive Derivative Free Method for Bayesian Posterior Approximation,
SPLetters(19), No. 2, February 2012, pp. 87-90.
IEEE DOI Link 1201
BibRef


Szlam, A.[Arthur], Guo, Z.H.[Zhao-Hui], Osher, S.J.[Stanley J.],
A split Bregman method for non-negative sparsity penalized least squares with applications to hyperspectral demixing,
ICIP10(1917-1920).
IEEE DOI Link 1009
BibRef

Li, B.[Bo], Liu, W.J.[Wen-Ju], Dou, L.H.[Li-Hua],
Learning GMM Using Elliptically Contoured Distributions,
ICPR10(511-514).
IEEE DOI Link 1008
Gaussian mixture model BibRef

Ji, Y.[Yangfeng], Lin, T.[Tong], Zha, H.B.[Hong-Bin],
CDP Mixture Models for Data Clustering,
ICPR10(637-640).
IEEE DOI Link 1008
BibRef

Ari, C.[Caglar], Aksoy, S.[Selim],
Maximum Likelihood Estimation of Gaussian Mixture Models Using Particle Swarm Optimization,
ICPR10(746-749).
IEEE DOI Link 1008
BibRef

Nielsen, F.[Frank], Boltz, S.[Sylvain], Schwander, O.[Olivier],
Bhattacharyya Clustering with Applications to Mixture Simplifications,
ICPR10(1437-1440).
IEEE DOI Link 1008
BibRef

Martinez-Uso, A.[Adolfo], Pla, F.[Filiberto], Sotoca, J.M.[Jose M.],
A Semi-supervised Gaussian Mixture Model for Image Segmentation,
ICPR10(2941-2944).
IEEE DOI Link 1008
BibRef

Nacereddine, N.[Nafaa], Tabbone, S.A.[Salavatore A.], Ziou, D.[Djemel], Hamami, L.[Latifa],
Asymmetric Generalized Gaussian Mixture Models and EM Algorithm for Image Segmentation,
ICPR10(4557-4560).
IEEE DOI Link 1008
BibRef

Nickisch, H.[Hannes], Rasmussen, C.E.[Carl Edward],
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models,
DAGM10(272-282).
Springer DOI Link 1009
BibRef

Wang, R.B.[Rong-Bo], Hou, C.H.[Chao-Huan], Chen, D.[Dong],
Blind separation of instantaneous linear mixtures of cyclostationary signals,
IASP10(492-495).
IEEE DOI Link 1004
BibRef

Garcia, V.[Vincent], Nielsen, F.[Frank], Nock, R.[Richard],
Levels of Details for Gaussian Mixture Models,
ACCV09(II: 514-525).
Springer DOI Link 0909
BibRef

Zhao, Q.P.[Qin-Pei], Hautamaki, V.[Ville], Karkkainen, I.[Ismo], Franti, P.[Pasi],
Random swap EM algorithm for finite mixture models in image segmentation,
ICIP09(2397-2400).
IEEE DOI Link 0911
BibRef

Mancera, L., Babacan, S.D.[S. Derin], Molina, R., Katsaggelos, A.K.,
Image restoration by mixture modelling of an overcomplete linear representation,
ICIP09(3949-3952).
IEEE DOI Link 0911
BibRef

Barcelos, C.A.Z.[Celia A. Zorzo], Chen, Y.M.[Yun-Mei], Chen, F.[Fuhua],
A soft multiphase segmentation model via Gaussian mixture,
ICIP09(4049-4052).
IEEE DOI Link 0911
BibRef

Dey, C.[Chandrama], Jia, X.P.[Xiu-Ping], Fraser, D., Wang, L.,
Mixed Pixel Analysis for Flood Mapping Using Extended Support Vector Machine,
DICTA09(291-295).
IEEE DOI Link 0912
BibRef

Otoom, A.F.[Ahmed Fawzi], Concha, O.P.[Oscar Perez], Gunes, H.[Hatice], Piccardi, M.[Massimo],
Mixtures of Normalized Linear Projections,
ACIVS09(66-76).
Springer DOI Link 0909
BibRef

Piccardi, M.[Massimo], Gunes, H.[Hatice], Otoom, A.F.[Ahmed Fawzi],
Maximum-likelihood dimensionality reduction in gaussian mixture models with an application to object classification,
ICPR08(1-4).
IEEE DOI Link 0812
See also Feature extraction techniques for abandoned object classification in video surveillance. BibRef

Horta, M.M.[Michelle M.], Mascarenhas, N.D.A.[Nelson D. A.], Frery, A.C.[Alejandro C.],
A comparison of clustering fully polarimetric SAR images using SEM algorithm and G0P mixture model with different initializations,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Reddy, C.K.[Chandan K.], Rajaratnam, B.[Bala],
Component-wise parameter smoothing for learning mixture models,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Mansjur, D.S.[Dwi Sianto], Fu, Q.A.[Qi-Ang], Juang, B.H.[Biing Hwang],
Utilizing non-uniform cost learning for active control of inter-class confusion,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Mansjur, D.S.[Dwi Sianto], Juang, B.H.[Biing Hwang],
Incremental learning of mixture models for simultaneous estimation of class distribution and inter-class decision boundaries,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Tang, H.[Hao], Huang, T.S.[Thomas S.],
Boosting Gaussian mixture models via discriminant analysis,
ICPR08(1-4).
IEEE DOI Link 0812
BibRef

Bordes, J.B., Prinet, V.,
Mixture Distributions for Weakly Supervised Classification in Remote Sensing Images,
BMVC08(xx-yy).
PDF Version. 0809
BibRef

Hou, S.[Shaobo], Galata, A.[Aphrodite],
Robust estimation of gaussian mixtures from noisy input data,
CVPR08(1-8).
IEEE DOI Link 0806
BibRef

Corona, E.[Enrique], Nutter, B.[Brian], Mitra, S.[Sunanda],
Optimized data-driven order selection method for Gaussian mixtures on clustering problems,
Southwest10(73-76).
IEEE DOI Link 1005
BibRef
Earlier:
Non-parametric Estimation of Mixture Model Order,
Southwest08(145-148).
IEEE DOI Link 0803
BibRef

Santos-Villalobos, H.J.[Hector J.], Boutin, M.[Mireille],
An empirical method for comparing the shape of two Gaussian mixtures,
ICIP10(4269-4272).
IEEE DOI Link 1009
recognize planar objects consisting of blobs. BibRef

Boutin, M.[Mireille], Comer, M.L.[Mary L.],
Faithful Shape Representation for 2D Gaussian Mixtures,
ICIP07(VI: 369-372).
IEEE DOI Link 0709
BibRef

Palazón, V.[Vicente], Marzal, A.[Andrés], Vilar, J.M.[Juan Miguel],
Cyclic Linear Hidden Markov Models for Shape Classification,
PSIVT07(152-165).
Springer DOI Link 0712
BibRef

Palazón, V.[Vicente], Marzal, A.[Andrés],
Cyclic Viterbi Score for Linear Hidden Markov Models,
IbPRIA07(II: 339-346).
Springer DOI Link 0706
BibRef

Romero, V.[Verónica], Giménez, A.[Adriŕ], Juan, A.[Alfons],
Explicit Modelling of Invariances in Bernoulli Mixtures for Binary Images,
IbPRIA07(I: 539-546).
Springer DOI Link 0706
See also Embedded Bernoulli Mixture HMMs for Continuous Handwritten Text Recognition. BibRef

Alabau, V.[Vicente], Casacuberta, F.[Francisco], Vidal, E.[Enrique], Juan, A.[Alfons],
Inference of Stochastic Finite-State Transducers Using N -Gram Mixtures,
IbPRIA07(II: 282-289).
Springer DOI Link 0706
BibRef

Bouguila, N.[Nizar], Ziou, D.[Djemel], Hammoud, R.I.[Riad I.],
A Bayesian Non-Gaussian Mixture Analysis: Application to Eye Modeling,
Learning07(1-8).
IEEE DOI Link 0706
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Wang, P.[Peng], Kohler, C.[Christian], Verma, R.[Ragini],
Estimating Cluster Overlap on Manifolds and its Application to Neuropsychiatric Disorders,
ComponentAnalysis07(1-6).
IEEE DOI Link 0706
BibRef

Luo, B.[Bin], Chen, S.B.[Si-Bao],
LPP and LPP Mixtures for Graph Spectral Clustering,
PSIVT06(118-127).
Springer DOI Link 0612
BibRef

Penalver Benavent, A.[Antonio], Escolano Ruiz, F.[Francisco], Saez Martinez, J.M.[Juan M.],
Two Entropy-Based Methods for Learning Unsupervised Gaussian Mixture Models,
SSPR06(649-657).
Springer DOI Link 0608
BibRef
Earlier:
EBEM: An Entropy-based EM Algorithm for Gaussian Mixture Models,
ICPR06(II: 451-455).
WWW Version. 0609
BibRef

Lin, B.[Bin], Wang, X.J.[Xian-Ji], Zhong, R.T.[Run-Tian], Zhuang, Z.Q.[Zhen-Quan],
Continuous Optimization based-on Boosting Gaussian Mixture Model,
ICPR06(I: 1192-1195).
WWW Version. 0609
BibRef

Ilonen, J., Paalanen, P., Kamarainen, J.K., Kalviainen, H.,
Gaussian mixture pdf in one-class classification: computing and utilizing confidence values,
ICPR06(II: 577-580).
WWW Version. 0609
BibRef

Lu, X.[Xiqun],
Joint Distributions based on DFB and Gaussian Mixtures for Evaluation of Style Similarity among Paintings,
ICPR06(II: 865-868).
WWW Version. 0609
BibRef

Chen, D.T.[Da-Tong], Yang, J.[Jie],
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models,
ICPR06(II: 1078-1081).
WWW Version. 0609
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Abd-Almageed, W.[Wael], Davis, L.S.[Larry S.],
Density Estimation Using Mixtures of Mixtures of Gaussians,
ECCV06(IV: 410-422).
Springer DOI Link 0608
BibRef

Zhu, Y.N.[Ya-Nong], Fisher, M.H.[Mark H.], Zwiggelaar, R.[Reyer],
Improving ASM Search Using Mixture Models for Grey-Level Profiles,
IbPRIA05(I:292).
Springer DOI Link 0509
BibRef

Ali, A.M.[Asem M.], Farag, A.A.[Amal A.], Farag, A.A.[Aly A.],
Labelling color images by modelling the colors density using a linear combination of Gaussians and EM algorithm,
ICIP09(1645-1648).
IEEE DOI Link 0911
BibRef

Ali, A.M.[Asem M.], Farag, A.A.[Aly A.],
Density estimation using a new AIC-type criterion and the EM algorithm for a linear combination of Gaussians,
ICIP08(3024-3027).
IEEE DOI Link 0810
BibRef

Farag, A.A., El-Baz, A., Gimel'farb, G.,
Density estimation using modified expectation-maximization algorithm for a linear combination of gaussians,
ICIP04(III: 1871-1874).
IEEE DOI Link 0505
BibRef
And: A3, A1, A2:
Expectation-maximization for a linear combination of Gaussians,
ICPR04(III: 422-425).
IEEE DOI Link 0409
BibRef

de Ridder, D., Franc, V.,
Robust subspace mixture models using t-distributions,
BMVC03(xx-yy).
HTML Version. 0409
BibRef

Cheung, Y.M.[Yiu-Ming],
A rival penalized EM algorithm towards maximizing weighted likelihood for density mixture clustering with automatic model selection,
ICPR04(IV: 633-636).
IEEE DOI Link 0409
BibRef

Sminchisescu, C.[Cristian], Jepson, A.D.[Allan D.],
Variational mixture smoothing for non-linear dynamical systems,
CVPR04(II: 608-615).
IEEE Abstract. 0408
BibRef

Huang, K.[Kun], Ma, Y.[Yi], Vidal, R.,
Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and its Applications,
CVPR04(II: 631-638).
IEEE Abstract. 0408
See also Generalized Principal Component Analysis (GPCA). See also Motion segmentation with missing data using powerfactorization and GPCA. BibRef

Vermaak, J., Doucet, A., Perez, P.,
Maintaining multi-modality through mixture tracking,
ICCV03(1110-1116).
IEEE DOI Link 0311
BibRef

Franc, V.[Vojtech], Hlavác, V.[Václav],
A Contribution to the Schlesinger's Algorithm Separating Mixtures of Gaussians,
CAIP01(169 ff.).
HTML Version. 0210
BibRef

Niemistö, A., Lukin, V.V., Shmulevich, I., Yli-Harja, O.[Olli], Dolia, A.,
A Training-based Optimization Framework for Misclassification Correction,
SCIA01(O-W2). 0206
BibRef

Xuan, G., Zhang, W., Chai, P.,
EM Algorithms of Gaussian Mixture Model and Hidden Markov Model,
ICIP01(I: 145-148).
IEEE Abstract. 0108
BibRef

Kudo, M., Imai, H., Shimbo, M.,
A Histogram-based Classifier on Overlapped Bins,
ICPR00(Vol II: 29-33).
IEEE DOI Link 0009
BibRef

Hammoud, R., Mohr, R.,
Mixture Densities for Video Objects Recognition,
ICPR00(Vol II: 71-75).
IEEE DOI Link 0009
BibRef

Zwart, J.P., Kröse, B.,
Constrained Mixture Modeling of Intrinsically Low-dimensional Distributions,
ICPR00(Vol II: 610-613).
IEEE DOI Link 0009
BibRef

Somol, P., Grim, J.[Jiri], Novovicova, J.[Jana], Pudil, P.[Pavel], Ferri, F.J.[Francesc J.],
Initializing Normal Mixtures of Densities,
ICPR98(Vol I: 886-890).
IEEE DOI Link 9808
BibRef

Kudo, M.[Mineichi], Shimbo, M.[Masaru], Sumiyoshi, S.[Satoru], Tenmoto, H.[Hiroshi],
A Subclass-Based Mixture Model for Pattern Recognition,
ICPR98(Vol I: 870-872).
IEEE DOI Link 9808
BibRef

Schultz, N.[Nette], Carstensen, J.M.[Jens Michael],
Bimodal histogram transformation based on maximum likelihood parameter estimates in univariate Gaussian mixtures,
CIAP97(II: 532-543).
WWW Version. 9709
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Mixed Pixels, Unmixing .


Last update:Feb 8, 2012 at 11:25:05