Keith Price Bibliography Mixture Models, Mixed Pixels

Bouguila, N.[Nizar], El Guebaly, W.[Walid],
Discrete data clustering using finite mixture models,
PR(42), No. 1, January 2009, pp. 33-42.
WWW Version. 0809
Discrete data; Finite mixture models; Multinomial; Generalized Dirichlet distribution; EM; Spatial color; Image databases; Labeled and unlabeled images; Summarization; Text classification BibRef

Bouguila, N.[Nizar],
Non-Gaussian mixture image models prediction,
ICIP08(2580-2583).
IEEE DOI Link 0810
BibRef

Boutemedjet, S.[Sabri], Bouguila, N.[Nizar], Ziou, D.[Djemel],
A Hybrid Feature Extraction Selection Approach for High-Dimensional Non-Gaussian Data Clustering,
PAMI(31), No. 8, August 2009, pp. 1429-1443.
IEEE DOI Link 0906
BibRef
Earlier:
Unsupervised Feature and Model Selection for Generalized Dirichlet Mixture Models,
ICIAR07(330-341).
Springer DOI Link 0708
Feature selection in mixtures BibRef

Jin, H.D.[Hui-Dong], Leung, K.S.[Kwong-Sak], Wong, M.L.[Man-Leung], Xu, Z.B.[Zong-Ben],
Scalable model-based cluster analysis using clustering features,
PR(38), No. 5, May 2005, pp. 637-649.
WWW Version. 0501
BibRef

Jin, H.D.[Hui-Dong], Wong, M.L.[Man-Leung], Leung, K.S.,
Scalable Model-Based Clustering for Large Databases Based on Data Summarization,
PAMI(27), No. 11, November 2005, pp. 1710-1719.
IEEE DOI Link 0510
BibRef

Aiyer, A.[Anuradha], Pyun, K.P.[Kyungsuk Peter], Huang, Y.Z.[Ying-Zong], O'Brien, D.B.[Deirdre B.], Gray, R.M.[Robert M.],
Lloyd clustering of Gauss mixture models for image compression and classification,
SP:IC(20), No. 5, June 2005, pp. 459-485.
WWW Version. 0506
BibRef

Pernkopf, F.[Franz], Bouchaffra, D.[Djamel],
Genetic-Based EM Algorithm for Learning Gaussian Mixture Models,
PAMI(27), No. 8, August 2005, pp. 1344-1348.
IEEE Abstract. IEEE Top Reference. 0506
BibRef

Zhang, B.B.[Bai-Bo], Zhang, C.S.[Chang-Shui], Yi, X.[Xing],
Active curve axis Gaussian mixture models,
PR(38), No. 12, December 2005, pp. 2351-2362.
WWW Version. 0510
BibRef

Ma, J.W.[Jin-Wen], Fu, S.Q.[Shu-Qun],
On the correct convergence of the EM algorithm for Gaussian mixtures,
PR(38), No. 12, December 2005, pp. 2602-2611.
WWW Version. 0510
BibRef

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

Kwan, C., Ayhan, B., Chen, G., Wang, J., Ji, B., Chang, C.I.,
A Novel Approach for Spectral Unmixing, Classification, and Concentration Estimation of Chemical and Biological Agents,
GeoRS(44), No. 2, February 2006, pp. 409-419.
IEEE DOI Link 0602
BibRef

Permuter, H.[Haim], Francos, J.[Joseph], 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

Rogge, D.M., Rivard, B., Zhang, J., Feng, J.,
Iterative Spectral Unmixing for Optimizing Per-Pixel Endmember Sets,
GeoRS(44), No. 12, December 2006, pp. 3725-3736.
IEEE DOI Link 0701
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. IEEE Top Reference. 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

Foody, G.M.[Giles M.], Doan, H.T.X.,
Variability in Soft Classification Prediction and Its Implications for Sub-pixel Scale Change Detection and Super Resolution Mapping,
PhEngRS(73), No. 8, August 2007, pp. 923-934.
WWW Version. 0709
The impacts of class spectral variability on unmixing the the implications for analyses based on soft classification outputs. BibRef

Jia, S.[Sen], Qian, Y.T.[Yun-Tao],
Spectral and Spatial Complexity-Based Hyperspectral Unmixing,
GeoRS(45), No. 12, December 2007, pp. 3867-3879.
IEEE DOI Link 0711
BibRef
Earlier:
Improved Stone's Complexity Pursuit for Hyperspectral Imagery Unmixing,
ICPR06(IV: 817-820).
WWW Version. 0609
BibRef
And:
MRF Based Spatial Complexity for Hyperspectral Imagery Unmixing,
SSPR06(531-540).
Springer DOI Link 0608
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

Berman, M.,
Some Unmixing Problems and Algorithms in Spectroscopy and Hyperspectral Imaging,
AIPR06(15-15).
IEEE DOI Link 0610
BibRef

Bruneau, P.[Pierrick], Gelgon, M.[Marc], Picarougne, F.[Fabien],
Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach,
ICPR08(1-4).
IEEE DOI Link 0812
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

Nguyen, T.M.[Thanh Minh], Wu, Q.M.J.[Q.M. Jonathan],
Maximum likelihood neural network based on the correlation among neighboring pixels for noisy image segmentation,
ICIP08(3020-3023).
IEEE DOI Link 0810
extended from Gaussian mixture model. 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],
Non-parametric Estimation of Mixture Model Order,
Southwest08(145-148).
IEEE DOI Link 0803
BibRef

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

Miao, L.[Lidan], Qi, H.R.[Hai-Rong],
A Constrained Non-Negative Matrix Factorization Approach to Unmix Highly Mixed Hyperspectral Data,
ICIP07(II: 185-188).
IEEE DOI Link 0709
BibRef

Sfikas, G.[Giorgos], Nikou, C.[Christophoros], Galatsanos, N.[Nikolaos],
Edge preserving spatially varying mixtures for image segmentation,
CVPR08(1-7).
IEEE DOI Link 0806
BibRef
Earlier:
Robust Image Segmentation with Mixtures of Student's t-Distributions,
ICIP07(I: 273-276).
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.[Adrià], 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
BibRef

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
BibRef

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.[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.[Allan],
Variational mixture smoothing for non-linear dynamical systems,
CVPR04(II: 608-615).
IEEE Abstract. IEEE Top Reference. 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. IEEE Top Reference. 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. IEEE Top Reference. 0108
BibRef

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

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

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

Last update:Nov 16, 2009 at 19:35:14