Model-Based Gaussian and Non-Gaussian Clustering, Biometrics, vol.49, issue.3, pp.803-821, 1993. ,
DOI : 10.2307/2532201
Unsupervised image segmentation using triplet Markov fields, Computer Vision and Image Understanding, vol.99, issue.3, pp.476-498, 2005. ,
DOI : 10.1016/j.cviu.2005.04.003
URL : https://hal.archives-ouvertes.fr/hal-01347961
Unsupervised statistical segmentation of non stationary images using triplet Markov Fields, IEEE Trans. PAMI, vol.29, issue.8, pp.367-1378, 2007. ,
Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986. ,
DOI : 10.1016/0031-3203(83)90012-2
Pattern Recognition and Machine Learning, 2006. ,
Markov random fields for textures recognition with local invariant regions and their geometric relationships, Procedings of the British Machine Vision Conference 2005, 2005. ,
DOI : 10.5244/C.19.72
URL : https://hal.archives-ouvertes.fr/inria-00548520
High-dimensional data clustering, Computational Statistics & Data Analysis, vol.52, issue.1, 2007. ,
DOI : 10.1016/j.csda.2007.02.009
URL : https://hal.archives-ouvertes.fr/inria-00548591
Bayesian Inference for Mixture: The Label Switching Problem, COMPSTAT 98, pp.227-232, 1998. ,
DOI : 10.1007/978-3-662-01131-7_26
EM procedures using mean field-like approximations for Markov model-based image segmentation, Pattern Recognition, vol.36, issue.1, pp.131-144, 2003. ,
DOI : 10.1016/S0031-3203(02)00027-4
URL : https://hal.archives-ouvertes.fr/inria-00072526
Gaussian parsimonious clustering models, Pattern Recognition, vol.28, issue.5, pp.781-793, 1995. ,
DOI : 10.1016/0031-3203(94)00125-6
URL : https://hal.archives-ouvertes.fr/inria-00074643
An iterative Gibbsian technique for reconstruction of m-ary images, Pattern Recognition, vol.22, issue.6, pp.747-761, 1989. ,
DOI : 10.1016/0031-3203(89)90011-3
Markov Random Field Texture Models, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.5, issue.1, p.2539, 1983. ,
DOI : 10.1109/TPAMI.1983.4767341
Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Statist. Soc. Ser. B, vol.39, pp.1-38, 1977. ,
Hidden markov random field model selection criteria based on mean field-like approximations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, issue.9, p.25, 2003. ,
DOI : 10.1109/TPAMI.2003.1227985
Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics, Genetics, vol.174, issue.2, pp.805-816, 2006. ,
DOI : 10.1534/genetics.106.059923
URL : https://hal.archives-ouvertes.fr/hal-00370263
Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images*, Journal of Applied Statistics, vol.1, issue.5-6, pp.721-741, 1984. ,
DOI : 10.1109/TIT.1972.1054786
Markov Random Fields: Interacting particle systems for image modelling and analysis, 1996. ,
Dicriminant analysis by Gaussian mixtures, J. Roy. Statist. Soc. Ser. B, vol.58, pp.158-176, 1996. ,
Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modeling, Statistical Science, vol.20, issue.1, 2005. ,
DOI : 10.1214/088342305000000016
Bayes Factors, Journal of the American Statistical Association, vol.2, issue.430, pp.733-795, 1995. ,
DOI : 10.1080/01621459.1995.10476572
Discriminative Random Fields, International Journal of Computer Vision, vol.21, issue.1, pp.179-201, 2006. ,
DOI : 10.1007/s11263-006-7007-9
URL : http://repository.cmu.edu/cgi/viewcontent.cgi?article=1360&context=robotics
Independence properties of directed markov fields, Networks, vol.5, issue.5, pp.491-505, 1990. ,
DOI : 10.1002/net.3230200503
Affine-invariant local descriptors and neighborhood statistics for texture recognition, Proceedings Ninth IEEE International Conference on Computer Vision, 2003. ,
DOI : 10.1109/ICCV.2003.1238409
URL : https://hal.archives-ouvertes.fr/inria-00548231
Ant colony optimization for image regularization based on a nonstationary Markov modeling, IEEE Trans. IP, vol.16, issue.3, pp.865-879, 2007. ,
URL : https://hal.archives-ouvertes.fr/hal-00159093
Clustering based on a multi-layer mixture model, J. Comput. Graph. Statist, vol.14, issue.3, 2005. ,
Markov random field modeling in computer vision, 1995. ,
DOI : 10.1007/978-4-431-66933-3
Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004. ,
DOI : 10.1023/B:VISI.0000029664.99615.94
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.4931
Pairwise Markov Random Fields and segmentation of textured images. Machine Graph. Vision, pp.705-718, 2000. ,
Estimation of Parameters in Hidden Markov Models, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol.337, issue.1647, pp.407-428, 1991. ,
DOI : 10.1098/rsta.1991.0132
Estimating the Dimension of a Model, The Annals of Statistics, vol.6, issue.2, pp.461-464, 1978. ,
DOI : 10.1214/aos/1176344136
Dealing with label switching in mixture models, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol.62, issue.4, pp.795-809, 2000. ,
DOI : 10.1111/1467-9868.00265
Statistical Learning Theory, 1998. ,
Gene Clustering via Integrated Markov Models Combining Individual and Pairwise Features, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.6, issue.2, 2007. ,
DOI : 10.1109/TCBB.2007.70248
URL : https://hal.archives-ouvertes.fr/hal-00781174
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