Wojciech Pieczynski

 

 

Address

:

TELECOM SudParis (ex TELECOM INT)
Département CITI, CNRS UMR 5157

9, Rue Charles Fourier
91011 Evry Cedex - FRANCE 

Room

:

D 205

Phone

:

+(33) 1.60.76.44.25

Fax

:

+(33) 1.60.76.44.33

Email

:

Wojciech.Pieczynski@it-sudparis.eu

 

 

 

 

Research Activities and Curriculum Vitae

Wojciech Pieczynski received the Doctorat d'Etat degree in Mathematical Statistics from the Université Pierre et Marie Curie, Paris, France, in 1986. He is currently Professor at the Telecom SudParis (ex Telecom INT), Head of the Communications, Image, and Information Processing (CITI) Department, and the Coordinator of the Modélisations Statistiques et Applications (MSA) 3rd Year Major. His research interests include mathematical statistics, stochastic processes and statistical image processing.

Publications and PhD students

Some of the publications below have appeared in an IEEE journal, Elsevier journal or conference record. By allowing you to download them, I am required to post the following copyright reminder: "This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

 


Journal articles 


 

[A70] M. Y. Boudaren, L. An, and W. Pieczynski, Unsupervised segmentation of SAR images using Gaussian mixture hidden evidential Markov fields, IEEE Geoscience and Remote Sensing Letters, accepted, October 2016.

[A69] I. Gorynin, S. Derrode, E. Monfini, and W. Pieczynski, Fast filtering in switching approximations of non-linear Markov systems with applications to stochastic volatility, IEEE Trans. on Automatic Control, accepted, May 2016.

[A68] M. Y. Boudaren and W. Pieczynski, Dempster-Shafer fusion of evidential pairwise Markov chains, IEEE Trans. on Fuzzy Systems, accepted, February 2016.

[A67] A. Habbouchi, M. Y. Boudaren, A. Aissani, and W. Pieczynski, Unsupervised segmentation of Markov random fields corrupted by nonstationary noise, IEEE Signal Processing Letters, Vol. 23, No. 11, pp. 1607-1611, 2016.

[A66] S. Derrode and W. Pieczynski, Unsupervised classification using hidden Markov chain with unknown noise copulas and margins, Signal Processing, Vol. 128, pp. 8-17, November 2016.

[A65] M. Y. Boudaren, L. An, and W. Pieczynski, Dempster-Shafer fusion of evidential pairwise Markov fields, International Journal of Approximate Reasoning, Vol. 74, pp. 13-29, July 2016.

[A64] M. Y. Boudaren and W. Pieczynski, Unified representation of sets of heterogeneous Markov transition matrices, IEEE Trans. on Fuzzy Systems, Vol. 24, No. 2, pp. 497-503, April 2016.

[A63] N. Abbassi, D. Benboudjema, S. Derrode, and W. Pieczynski, Optimal filter approximations in Conditionally Gaussian Pairwise Markov Switching Models, IEEE Trans. on Automatic Control, Vol. 60, No. 4, pp. 1104-1109, April 2015.

[A62] M. Y. Boudaren, E. Monfrini, W. Pieczynski, and A. Aissani, Phasic triplet Markov chains, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 36, No. 11, pp. 2310 - 2316, November 2014.

[A61] N. Abbassi, S. Derrode, F. Desbouvries, Y. Petetin, and W. Pieczynski, Filtrage statistique optimal rapide dans des systèmes linéaires à sauts non stationnaires, Traitement du Signal, Vol. 31, No. 3-4, pp. 339-361, 2014.

[A60] S. Derrode, L. Benyoussef, and W. Pieczynski, Subsampling-based HMC parameters estimation with application to large data sets classification, Signal, Image and Video Processing, Vol. 8, No. 5, pp. 873-882, June 2014.

[A59] S. Derrode and W. Pieczynski, Exact fast computation of optimal filter in Gaussian switching linear systems, IEEE Signal Processing Letters, Vol. 20, No. 7, pp. 701-704, July 2013.

[A58] S. Derrode and W. Pieczynski, Unsupervised data classification using pairwise Markov chains with automatic copulas selection, Computational Statistics and Data Analysis, Vol. 63, pp. 81-98, July 2013.

[A57] M. Castella, S. Rafi, P. Comon, and W. Pieczynski, Separation of instantaneous mixtures of dependent sources using classical ICA methods, EURASIP Journal on Advances in Signal Processing, No. 62, 2013.

[A56] M. Y. Boudaren, E. Monfrini, and W. Pieczynski, Unsupervised segmentation of random discrete data hidden with switching noise distributions, IEEE Signal Processing Letters, Vol. 19, No. 10, pp. 619-622, October 2012.

[A55] M. Y. Boudaren, E. Monfrini, W. Pieczynski, and A. Assani, Dempster-Shafer fusion of multisensor signals in nonstationary Markovian context, EURASIP Journal on Advances in Signal Processing, No. 134, 2012.

[A54] S. Derrode and W. Pieczynski, Segmentation d’images par modèle de mélange conjoint non gaussien, Traitement du Signal, Vol. 29, No. 1-2, 99. 9-28, 2012.

[A53] J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised segmentation of hidden semi-Markov non stationary chains, Signal Processing, Vol. 92, No. 1, pp. 29–42, January 2012.

[A52] W. Pieczynski, Exact smoothing in hidden conditionally Markov switching linear models, Communications in Statistics - Theory and Methods, Vol. 40, No. 16, pp. 2823 - 2829, May 2011.

[A51] W. Pieczynski, Exact filtering in conditionally Markov switching hidden linear models, Comptes Rendus Mathematique, Vol. 349, No. 9-10, pp. 587-590, May 2011.

[A50] P. Lanchantin, J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise, Signal Processing, Vol. 91, No. 2, pp. 163-175, February 2011.

[A49] J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise, Signal Processing, Vol. 90, No. 11, pp. 2899-2910, November 2010.

[A48] N. Brunel, J. Lapuyade-Lahorgue, and W. Pieczynski, Modeling and unsupervised classification of multivariate hidden Markov chains with copulas, IEEE Trans. on Automatic Control, Vol. 55, No. 2, pp. 338-349, February 2010.

[A47] I. Karoui, R. Fablet, J.-M. Boucher, W. Pieczynski and J.-M. Augustin, Fusion of textural statistics using a similarity measure: application to texture recognition and segmentation, Pattern Analysis & Applications,  Vol. 11, No. 3-4, pp; 425-434, September 2008.

[A46] P. Lanchantin, J. Lapuyade-Lahorgue, and W. Pieczynski, Unsupervised segmentation of triplet Markov chains hidden with long-memory noise, Signal Processing, No. 88, Vol. 5, pp 1134-1151, May 2008.

[A45] W. Pieczynski, Sur la convergence de l’estimation conditionnelle itérative, Comptes Rendus de l’Académie des Sciences-Mathématique, Vol. 346, No. 7-8, pp. 457-460, Avril 2008.

[A44] D. Benboudjema and W. Pieczynski, Unsupervised statistical segmentation of non stationary images using triplet Markov fields, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 29, No. 8, pp. 1367-1378, 2007.

[A43] W. Pieczynski, Multisensor triplet Markov chains and theory of evidence, International Journal of Approximate Reasoning, Vol. 45, No. 1, pp. 1-16, 2007.

[A42] F. Desbouvries, J. Lecomte, and W. Pieczynski, Kalman filtering in pairwise Markov trees, Signal Processing, Vol. 86, No. 5, pp. 1049-1054, 2006.

[A41] W. Pieczynski and D. Benboudjema, Multisensor triplet Markov fields and theory of evidence, Image and Vision Computing, Vol. 24, No. 1, pp. 61-69, 2006.

[A40] N. Brunel and W. Pieczynski, Unsupervised signal restoration using hidden Markov chains with copulas, Signal Processing, Vol. 85, No. 12, pp. 2304-2315, 2005.

[A39] D. Benboudjema and W. Pieczynski, Unsupervised image segmentation using triplet Markov fields, Computer Vision and Image Understanding, Vol. 99, No. 3, pp. 476-498, 2005.

[A38] W. Pieczynski, Copules gaussiennes dans les chaînes triplet partiellement de Markov - Gaussian copulas in triplet partially Markov chains, Comptes Rendus de l’Académie des Sciences – Mathématique, Vol. 341, No. 3,pp. 189-194, 2005.

[A37] P. Lanchantin and W. Pieczynski, Unsupervised restoration of hidden non stationary Markov chain using evidential priors, IEEE Trans. on Signal Processing, Vol. 53, No. 8, pp. 3091-3098, 2005.

[A36] E. Monfrini et W. Pieczynski, Estimation de mélanges généralisés dans les arbres de Markov cachés, application à la segmentation des images de cartons d’orgue de barbarie, Traitement du Signal, Vol. 22, No. 2, pp. 135-147, 2005.

[A35] P. Lanchantin et W. Pieczynski, Chaînes et arbres de Markov évidentiels avec applications à la segmentation des processus non stationnaires, Traitement du Signal, Vol. 22, No. 1, pp. 15-26, 2005.

[A34] W. Pieczynski, Fusion de Dempster-Shafer dans les chaînes triplet partiellement de Markov - Dempster-Shafer fusion in triplet partially Markov chains, Comptes Rendus de l’Académie des Sciences – Mathématique, Vol. 339, No. 11, pp. 797-802, 2004.

[A33] G. Mercier, S. Derrode et W. Pieczynski, Segmentation multi-échelle de nappes d'hydrocarbures, Traitement du Signal, Vol. 21, No. 4, pp. 329-346, 2004.

[A32] S. Derrode and W. Pieczynski, Signal and image segmentation using Pairwise Markov chains, IEEE Trans. on Signal Processing, Vol. 52, No. 9, pp. 2477-2489, 2004.

[A31] W. Pieczynski, Modèles de Markov en traitement d'images, Traitement du Signal, Vol. 20, No. 3, pp. 255-278, 2003.

[A30] W. Pieczynski, Arbres de Markov Triplet et fusion de Dempster-Shafer - Triplet Markov Trees and Dempster-Shafer fusion, Comptes Rendus de l’Académie des Sciences – Mathématique, Série I, Vol. 336, No. 10, pp. 869-872, 2003.

[A29] W. Pieczynski, Pairwise Markov chains, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 25, No. 5, pp. 634-639, 2003.

[A28] F. Desbouvries et W. Pieczynski, Modèles de Markov Triplet et filtrage de Kalman - Triplet Markov Models and Kalman filtering, Comptes Rendus de l’Académie des Sciences – Mathématique, Série I, Vol. 336, No. 8, pp. 667-670, 2003.

[A27] R. Fjortoft, Y. Delignon, W. Pieczynski, M. Sigelle, and F. Tupin, Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields, IEEE Trans. on Geoscience and Remote Sensing, Vol. 41, No. 3, pp. 675- 686, 2003.

[A26] W. Pieczynski, Chaînes de Markov Triplet, Triplet Markov Chains, Comptes Rendus de l’Académie des Sciences – Mathématique,  Série I, Vol. 335, No. 3, pp. 275-278, 2002.

[A25] W. Pieczynski, Arbres de Markov Couple, Pairwise Markov Trees, Comptes Rendus de l’Académie des Sciences – Mathématique,  Série I, Vol. 335, No. 1, pp. 79-82, 2002.

[A24] Y. Delignon and W. Pieczynski, Modeling non-Rayleigh speckle ditribution in SAR images, IEEE Trans. on Geoscience and Remote Sensing, Vol. 40, No. 6, pp. 1430-1435, 2002.

[A23] A. Bendjebbour, Y. Delignon, L. Fouque, V. Samson,  and W. Pieczynski, Multisensor Images Segmentation Using Dempster-Shafer Fusion in Markov Fields Context, IEEE Trans. on Geoscience and Remote Sensing, Vol. 39, No. 8, pp. 1789-1798, 2001.

[A22] W. Pieczynski and A.-N. Tebbache, Pairwise Markov random fields and segmentation of textured images, Machine Graphics & Vision, Vol. 9, No. 3, pp. 705-718, 2000.

[A21] W. Pieczynski, J. Bouvrais, and C. Michel, Estimation of generalized mixture in the case of correlated sensors, IEEE Trans. on Image Processing, Vol. 9, No. 2, pp. 308-311, 2000.

[A20] F. Salzenstein, W. Pieczynski, Sur le choix de méthode de segmentation statistique d'images, Traitement du Signal, Vol. 15, No. 2, pp. 120-127, 1998.

[A19] A. Bendjebbour, W. Pieczynski, Segmentation d'images multisenseur par fusion évidentielle dans un contexte markovien, Traitement du Signal, Vol. 14, No. 5, May 1997, pp. 453-464.

[A18] Y. Delignon, A. Marzouki, W. Pieczynski, Estimation of generalized mixture and its application in image segmentation, IEEE Trans. on Image Processing, Vol. 6, No. 10, pp. 1364-1375, 1997.

[A17] F. Salzenstein, W. Pieczynski, Parameter Estimation in hidden fuzzy Markov random fields and image segmentation, CVGIP : Graphical Models and Image Processing, Vol. 59, No. 4, pp. 205-220, 1997.

[A16] N. Giordana, W. Pieczynski, Estimation of generalized multisensor hidden Markov chains and unsupervised image segmentation, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 19, No. 5, pp. 465-475, 1997.

[A15] H. Caillol, W. Pieczynski, A. Hillon, Estimation of fuzzy Gaussian mixture and unsupervised statistical image segmentation, IEEE Trans. on Image Processing, Vol. 6, No. 3, pp. 425-440, 1997.

[A14] H. C. Quelle, J. M. Boucher, W. Pieczynski, Adaptive parameter estimation and unsupervised image segmentation, Machine Graphics & Vision, Vol. 5, No. 4, pp. 613-631, 1996.

[A13] B. Benmiloud, W. Pieczynski, Estimation des paramètres dans les chaînes de Markov cachées et segmentation d'images, Traitement du Signal, Vol. 12, No. 5, pp. 433-454 1995.

[A12] A. Peng, W. Pieczynski, Adaptive mixture estimation and unsupervised local Bayesian image segmentation, CVGIP: Graphical Models and Image Processing, Vol. 57, No. 5, pp. 389-399, 1995.

[A11] W. Pieczynski, Champs de Markov cachés et estimation conditionnelle itérative, Traitement du Signal, Vol. 11, No. 2, pp. 141-153, 1994.

[A10] W. Pieczynski, J.-M. Cahen, Champs de Markov flous cachés et segmentation d'images, Revue de Statistique Appliquée, Vol. 42, No. 3, pp. 13-31, 1994.

[A9] P. Masson, W. Pieczynski, SEM algorithm and unsupervised statistical segmentation of satellite images, IEEE Trans. on Geoscience and Remote Sensing, Vol. 34, No. 3, pp. 618-633, 1993.

[A8] H. Caillol, A. Hillion, W. Pieczynski, Fuzzy random fields and unsupervised image segmentation, IEEE Trans. on Geoscience and Remote Sensing, Vol. 34, No. 4,, pp. 801-810, 1993.

[A7] B. Braathen, W. Pieczynski, P. Masson, Global and local methods of unsupervised Bayesian segmentation of images, Machine Graphics & Vision, Vol. 2, No. 1, pp. 39-52, 1993.

[A6] N. Marhic, P. Masson, W. Pieczynski, Mélange de lois et segmentation non supervisée des données SPOT, Statistique et Analyse des Données, Vol. 16, No. 2, pp. 59-81, 1991.

[A5] W. Pieczynski, Estimation of context in random fields, Journal of Applied Statistics, Vol. 16(2), pp. 283-290, 1989.

[A4] W. Pieczynski, L'application de la méthode de la décantation dans un processus autorégressif, Comptes Rendus de l’Académie des Sciences – Mathématique, Paris, T. 308, Série I, pp. 583-585, 1989.

[A3] W. Pieczynski, Time series and counting estimation, Statistique et Analyse des Données, Vol. 14, No. 3, pp. 29-37, 1989.

[A2] W. Pieczynski, On the maximum likelihood estimation in the case of dependent random variables, Publications del’Institut de Statistique de l’Université  de Paris, Vol. 33, No. 2, pp. 79-87, 1988.

[A1] W. Pieczynski, Sur la méthode du maximum de vraisemblance dans le cas des observations dépendantes, Comptes Rendus de l’Académie des Sciences – Mathématique,  Série I, T. 304, 1987.

 


Book Chapters


[B4] W. Pieczynski, Exact calculation of optimal filter in hidden Markov switching long-memory chains, in Essays on Mathematics and Statistics: Volume 3, Athens Institute for Education and Research, Vladimir Akis, Editor, 2013.

[B3] S. Derrode and W. Pieczynski, Modèles de mélange à copules : simulation, restauration et sélection, In Avancées Récentes en Reconnaissance Statistique de Formes, Editeurs : F. Ghorbel, S. Derrode et O. Alata, 2012.

[B2] W. Pieczynski, Triplet Markov chains and image segmentation, draft of chapter 4 in Inverse problems in Vision and 3D Tomography, A. Mohammed-Djafari ed., Wiley, 2010 (English version of [B1]).

[B1] W. Pieczynski, Chaînes de Markov triplets et segmentation des images, draft du chapitre 4 du tome 1 de Problèmes inverses en imagerie et en vision, A. Mohammed-Djafari ed., Hermes, 2009 (version française de [B2]).

 


Conference articles


 

[C125] L. An, M. Li, M. E. Y Boudaren, and W. Pieczynski, Evidential Correlated Gaussian Mixture Markov Model for Pixel Labeling Problem, 4th International Conference on Belief Functions (BELIEF 2016), Prague, Czech Republic, September 21-23, 2016.

[C124] I. Gorynin, E. Monfrini, and W. Pieczynski, Unsupervised Learning Of Markov-Switching Stochastic Volatility With Application To Market Data, IEEE Machine Learning for Signal Processing Workshop (MLSP 2016), Salerno, Italy, 13-16 September, 2016.

[C123] F. Zheng, S. Derrode, and W. Pieczynski, Parameter Estimation In Conditionally Gaussian Pairwise Markov Switching Models And Unsupervised Smoothing, IEEE Machine Learning for Signal Processing Workshop (MLSP 2016), Salerno, Italy, 13-16 September, 2016.

[C122] I. Gorynin, L. Crélier, H. Gangloff, E. Monfini, and W. Pieczynski, Performance comparison across hidden, pairwise and triplet Markov models’ estimators, 5th International Conference on Applied and Computational Mathematics (ICACM '16), Mallorca, Spain, August 19-21, 2016.

[C121] I. Gorynin, E. Azeraf, W. Sabbagh, E. Monfini, and W. Pieczynski, Optimal filtering in hidden and pairwise Gaussian Markov systems, 5th International Conference on Applied and Computational Mathematics (ICACM '16), Mallorca, Spain, August 19-21, 2016.

[C120] I. Gorynin, E. Monfini, and W. Pieczynski, Fast filtering with new sparse transition Markov chains, 2016 IEEE Statistical Signal Processing Workshop (SSP 2016), Palma de Mallorca, Spain, June 26-29, 2016.

[C119] I. Gorynin, S. Derrode, E. Monfini, and W. Pieczynski, Lissage rapide dans des modèles non linéaires et non gaussiens, GRETSI, Lyon, France, 8-11 septembre 2015.

[C118] I. Gorynin, S. Derrode, E. Monfini, and W. Pieczynski, Exact fast smoothing in switching models with application to stochastic volatility, EUSIPCO 2015, Nice, France, 31 August - 4 September, 2015.

[C117] S. Derrode and W. Pieczynski, Fast Filter in Nonlinear Systems with Application to Stochastic Volatility Model, EUSIPCO 2014, Lisbon, Portugal, 1-5 September, 2014.

[C116] H. Hanzouli, J. Lapuyade-Lahorgue, E. Monfrini, G. Delso, W. Pieczynski, D. Visvikis, M. Hatt, PET/CT image denoising and segmentation based on a multi observation and multi scale Markov tree model, IEEE Nuclear Science Symposium and Medical Imaging Conference, Seoul, Korea, October 27-November, 2013.

[C115] D. Benboudjema, N. Othman, B. Dorizzi, and W. Pieczynski, Segmentation d’images des yeux par champs de Markov triplets: Applications à la biométrie, GRETSI 2013, 3-6 septembre, Brest, France, 2013.

[C114] S. Derrode and W. Pieczynski, Filtrage exact dans les systèmes linaires à sauts markoviens, GRETSI 2013, 3-6 septembre, Brest, France, 2013.

[C113] D. Benboudjema, N. Othman, B. Dorizzi, and W. Pieczynski, Challenging eye segmentation using triplet Markov spatial models, International Conference on Acoustics, Speech and Signal Processing (ICASSP), 26-31 May, Vancouver, Canada, 2013.

[C112] W. Pieczynski, S. Derrode, N. Abassi, Y. Petetin, and F. Desbouvries, Exact optimal filtering in an approximating switching system, Traitement et Analyse de l’Information - Méthodes et Applications (TAIMA), Hammamet, Tunisie, Mai 2013 .

[C111] M. Y. Boudaren, E. Monfrini, and W. Pieczynski, Unsupervised segmentation of nonstationary pairwise Markov chains using evidential priors, 20 th European Signal Processing Conference (EUSIPCO 2012), Bucharest, Romania, August 27-31, 2012.

[C110] S. Derrode and W. Pieczynski, Copulas selection in pairwise Markov chain, 20th International Conference on Computational Statistics (COMPSTAT 2012), Limassol, Cyprus, August, 27-31, 2012.

[C109] S. Derrode and W. Pieczynski, Segmentation conjointe d'images et copules, Ateliers Traitement et Analyse de l'Information : Méthodes et Applications, (TAIMA'11), Hammamet, Tunisia, 3-8 octobrte, 2011.

[C108] N. Abbassi, D. Benboudjema et W. Pieczynski, Filtrage optimal dans les systèmes linéaires gaussiens markoviens à sauts, GRETSI 2011, 5-8 septembre 2011, Bordeaux, France, 2011.

[C107] S. Rafi, M. Castella, et W. Pieczynski, Une extension avec variables latentes du modèle ICA, GRETSI 2011, 5-8 septembre 2011, Bordeaux, France, 2011.

[C106] E. Monfrini et W. Pieczynski, Arbres de Markov couple et segmentation non supervisee d’images: cas de la mono-résolution, GRETSI 2011, 5-8 septembre 2011, Bordeaux, France, 2011.

[C105] M. Y. Boudaren, W. Pieczynski, and E. Monfrini, Unsupervised Segmentation of Switching Pairwise Markov Chains, 7th International Symposium on Image and Signal Processing and Analysis (ISPA 2011), September 4-6, 2011, Dubrovnik, Croatia.

[C104] S. Derrode and W. Pieczynski, Unsupervised Restoration in Gaussian Pairwise Mixture Model, 2011 European Signal Processing Conference (EUSIPCO 2011), Barelona, Spain,, August 29-September 2, 2011.

[C103] M. Y. Boudaren, E. Monfrini, and W. Pieczynski, Switching Markov chains for non stationary images segmentation, IADIS Computer Graphics, Visualization, Computer Vision and Image Processing (CGVCVIP) 2011 Conference, July 20-26, Rome, Italy, 2011.

[C102] N. Abbassi, D. Benboudjema, and W. Pieczynski, Kalman filtering approximations in triplet Markov Gaussian switching models, IEEE Workshop on Statistical Signal Processing (SSP2011), Nice, France, June 28-30, 2011.

[C101] D. Benboudjema, M. El Bouchraya Malainin, and W. Pieczynski, Exact Kalman filtering in pairwise Gaussian switching systems, Applied Stochastic Models and Data Analysis, ASMDA 2011, June 7-10, Rome, Italy, 2011.

[C100] S. Rafi, M. Castella and W. Pieczynski, An extension of the ICA model using latent variable. Proc. of ICASSP, 22-27 May, Prague, Czech Republic, 2011.

[C99] M. Y. Boudaren, W. Pieczynski, and E. Monfrini, Unsupervised segmentation of non stationary data hidden with non stationary noise, 7th International Workshop on Systems, Signal Processing and their Applications (WOSSPA 2011), Tipaza, Algeria, May 9-11, 2011

[C98] S. Rafi, M. Castella and W. Pieczynski, Pairwise Markov model applied to unsupervised image separation, IASTED International Conference on Signal Processing, Pattern Recognition, and Applications (SPPRA), 16-18 February, Innsbruck, Austria, 2011.

[C97] W. Pieczynski, EM and ICE in hidden and triplet Markov models, Stochastic Modeling Techniques and Data Analysis international conference (SMTDA '10), Chania, Greece, June 8-11, 2010.

[C96] N. Abbassi and W. Pieczynski, Long memory based approximation of filtering in non linear switching systems, Stochastic Modeling Techniques and Data Analysis international conference (SMTDA '10), Chania, Greece, June 8-11, 2010.

[C95] N. Bardel, N. Abbassi, F. Desbouvries, W. Pieczynski and F. Barbaresco, A Bayesian filtering algorithm in Jump-Markov systems with application to Track-Before-Detect, IEEE International Radar Conference, Washington DC, USA, May 10-14, 2010.

[C94] W. Pieczynski and F. Desbouvries, Exact Bayesian smoothing in triplet switching Markov chains, Complex data modeling and computationally intensive statistical methods for estimation and prediction (S. Co 2009), September 14-16, Milan, Italy, 2009.

[C93] N. Abbassi et W. Pieczynski, Filtrage exact partiellement non supervisé dans les modèles cachés à sauts markoviens, GRETSI 2009, Dijon, 8-11 septembre 2009.

[C92] W. Pieczynski et F. Salzenstein, Lissage exact dans les arbres aléatoires triplets à sauts markoviens, GRETSI 2009, Dijon, 8-11 septembre 2009.

[C91] W. Pieczynski and N. Abbassi, Exact filtering and smoothing in short or long memory stochastic switching systems, 2009 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2009), September 2-4, Grenoble, France, 2009.

[C90] F. Forbes and W. Pieczynski, New trends in Markov models and related learning to restore data, 2009 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2009), September 2-4, Grenoble, France, 2009.

[C89] W. Pieczynski, Exact Smoothing in Hidden Conditionally Markov Switching Chains, XIII International Conference Applied Stochastic Models and Data Analysis, (ASMDA 2009), June 30- July 3, Vilnius Lithuania, 2009.

[C88] W. Pieczynski, N. Abbassi, and M. Ben Mabrouk,  Exact Filtering and Smoothing in Markov Switching Systems Hidden with Gaussian Long Memory Noise, XIII International Conference Applied Stochastic Models and Data Analysis, (ASMDA 2009), June 30- July 3, Vilnius Lithuania, 2009.

[C87] W. Pieczynski, Exact Calculation of Optimal Filter in Hidden Markov Switching Long-Memory Chain, 3rd International Conference on Mathematics and Statistics (ICMS 2009), 15-18 June 2009, Athens, Greece, 2009.

[C86] W. Pieczynski, Exact calculation of optimal filter in semi-Markov switching model, Fourth World Conference of the International Association for Statistical Computing (IASC 2008), December 5-8, Yokohama, Japan, 2008.

[C85] J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised segmentation of non-stationary hidden Markov chains with copulas, Fourth World Conference of the International Association for Statistical Computing (IASC 2008), December 5-8, Yokohama, Japan, 2008.

[C84] W. Pieczynski, Pairwise and uniformly hidden Markov fields, Sixth International Conference of Computational Methods in Sciences and Engineering (ICCMSE 2008), September, 25-30, Hersonissos, Crete, Grece, 2008.

[C83] N. Abbassi and W. Pieczynski, Exact filtering in semi-Markov jumping system, Sixth International Conference of Computational Methods in Sciences and Engineering (ICCMSE 2008), September, 25-30, Hersonissos, Crete, Grece, 2008.

[C82] D. Benboudjema, F. Tupin, W. Pieczynski,M. Sigelle and J.-M. Nicolas, Modélisation et segmentation non supervisée d’images RSO par champs de Markov triplets et lois de Fisher, GRETSI 2007, Troyes, France, 11-14 septembre 2007.

[C81] W. Pieczynski, Convergence of the iterative conditional estimation and application to mixture proportion identification, IEEE Statistical Signal Processing Workshop, SSP 2007, Madison, Wisconsin, USA, 26-29 August, 2007.

[C80] D. Benboudjema, F. Tupin, W. Pieczynski, M. Sigelle and J.-M. Nicolas, Unsupervised segmentation of SAR images using triplet Markov fields and Fisher noise distributions, IEEE International Geoscience and Remote Sensing Symposium (IGARSS 07), Barcelona, Spain, 23-27 July 2007.

[C79] M. Ben Mabrouk and W. Pieczynski, Unsupervised segmentation of random discrete data using triplet Markov chains, International Symposium on Applied Stochastic Models and Data Analysis, ASMDA 2007, Crete, Greece, May 2007.

[C78] J. Lapuyade-Lahorgue and W. Pieczynski, Partially Markov models and unsupervised segmentation of semi-Markov chains hidden with long dependence noise, International Symposium on Applied Stochastic Models and Data Analysis, ASMDA 2007, Crete, Greece, May 2007.

[C77] G. Mercier, S. Derrode, W. Pieczynski, J.-M. Nicolas, A. Joannic-Chardin, and J. Inglada, Copula-based stochastic kernels for abrupt change detection, IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2006, Denver, Colorado, July 31-August 4, 2006.

[C76] J. Lapuyade-Lahorgue and W. Pieczynski, Unsupervised segmentation of hidden semi-Markov non stationary chains, Twenty six International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2006, Paris, France, July 8-13, 2006.

[C75] D. Benboudjema and W. Pieczynski, Unsupervised segmentation of non stationary images with non Gaussian correlated noise using triplet Markov fields and the Pearson system, ICASSP 2006, Toulouse, France, May 15-19, 2006.

[C74] S. Derrode, L. Benyoussef, and W. Pieczynski, Contextual estimation of hidden Markov chains with application to image segmentation, ICASSP 2006, Toulouse, May 15-19, 2006.

[C73] D. Benboudjema and W. Pieczynski, Segmenting non stationary images with triplet Markov fields, International Conference on Image Processing (ICIP 2005), Genova, Italy, September 11-14, 2005.

[C72] N. Brunel, F. Barbaresco, et W. Pieczynski, Chaînes de Markov cachées multivariées à bruit corrélé non gaussien, avec applications à la segmentation du signal, GRESI 2005, Louvain-La-Neuve, Belgique, 6-9 septembre 2005.

[C71] D. Benboudjema et W. Pieczynski, Segmentation non supervisées dimages non stationnaires avec champs de Markov évidentiels, GRESI 2005, Louvain-La-Neuve, Belgique, 6-9 septembre 2005.

[C70] W. Pieczynski, Modeling non stationary hidden semi-Markov chains with triplet Markov chains and theory of evidence, Statistical Signal Processing (SSP2005), Bordeaux, France, July 17-20, 2005.

[C69] N. Brunel and W. Pieczynski, Modeling temporal dependence of Spherically Invariant Random Vectors with triplet Markov chains, Statistical Signal Processing (SSP2005), Bordeaux, France, July 17-20, 2005.

[C68] W. Pieczynski and P. Lanchantin, Restoring hidden non stationary process using triplet partially Markov chain with long memory noise, Statistical Signal Processing (SSP2005), Bordeaux, France, July 17-20, 2005.

[C67] W. Pieczynski and F. Desbouvries, On triplet Markov chains, International Symposium on Applied Stochastic Models and Data Analysis, (ASMDA 2005), Brest, France, May 2005.

[C66] N. Brunel, W. Pieczynski and S. Derrode, Copulas in vectorial hidden Markov chains for multicomponent image segmentation, ICASSP'05, Philadelphia, USA, March 2005.

[C65] J. Lecomte, F. Desbouvries and W. Pieczynski, A multiscale smoothing algorithm for pairwise Markov trees, Proceedings of the IMA sixth International Conference on Mathematics in Signal Processing, Cirencester, Great Britain, December 2004.

[C64] P. Lanchantin and W. Pieczynski, Unsupervised non stationary image segmentation using triplet Markov chains, Advanced Concepts for Intelligent Vision Systems (ACVIS 04), Aug. 31-Sept. 3, Brussels, Belgium, 2004.

[C63] D. Benboudjema and W. Pieczynski, Parameter estimation in pairwise Markov fields, Advanced Concepts for Intelligent Vision Systems (ACVIS 04), Aug. 31-Sept. 3, Brussels, Belgium, 2004.

[C62] W. Pieczynski, Triplet Partially Markov Chains and Tree, 2nd International Symposium on Image/Video Communications over fixed and mobile networks (ISIVC04), Brest, France 7 - 9 july, 2004

[C61] S. Derrode et W. Pieczynski, Segmentation non supervisée d'images par chaîne de Markov couple, Ateliers Traitement et Analyse de l'Information : Méeshodes et Applications (TAIMA'03), Hammamet, Tunisie, 26 september - 3 octobre, 2003.

[C60] N. Brunel and W. Pieczynski, Unsupervised signal restoration using Copulas and Pairwise Markov chains, IEEE Workshop on Statistical Signal Processing (SSP 2003), Saint Louis, Missouri, September 28-October 1, 2003.

[C59] E. Monfrini, J. Lecomte, F. Desbouvries, and W. Pieczynski, Image and Signal Restoration using Pairwise Markov Trees, IEEE Workshop on Statistical Signal Processing (SSP 2003), Saint Louis, Missouri, September 28-October 1, 2003.

[C58] S. Derrode, G. Mercier, and W. Pieczynski, Unsupervised multicomponent image segmentation combining a vectorial HMC model and ICA, 2003 International Conference on Image Processing (ICIP 2003), Barcelona, Spain, September 14-17, 2003.

[C57] E. Monfrini et W. Pieczynski, Segmentation non supervisée des images par les arbres de Markov couple, Actes du Colloque GRETSI03, Paris, 8-11 septembre, 2003.

[C56] P. Lanchantin et W. Pieczynski, Arbres de Markov Triplet et théorie de l’évidence, Actes du Colloque GRETSI03, Paris, 8-11 septembre, 2003.

[C55] G. Mercier, S. Derrode, W. Pieczynski, JM. Lecaillec et R. Garello, Multiscale oil slick segmentation with Markov chain model, IGARSS'03, Toulouse, France, 2125 July, 2003.

[C54] S. Derrode, G. Mercier, and W. Pieczynski, Unsupervised change detection in SAR images using a multicomponent HMC model, Proceedings of the Second International Workshop on the Analysis of Multitemporal Remote Sensing Images, Ispra, Italy,  July 16-18, 2003.

[C53] F. Desbouvries and W. Pieczynski, Particle Filtering in Pairwise and Triplet Markov Chains, Proceedings of the IEEE EURASIP Workshop on Nonlinear Signal and Image Processing (NSIP 2003), Grado-Gorizia, Italy, June 8-11, 2003.

[C52] F. Desbouvries and W. Pieczynski, Particle filtering with Pairwise Markov Processes, International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hong-Kong, April 2003.

[C51] W. Pieczynski and F. Desbouvries, Kalman Filering using Pairwise Gaussian Models, International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hong-Kong, April 2003.

[C50] W. Pieczynski, D. Benboudjema, and P. Lanchantin, Statistical image segmentation using Triplet Markov Fields, SPIEs International Symposium on Remote Sensing, September 22-27, Crete, Greece, 2002.

[C49] W. Pieczynski, C. Hulard, and T. Veit, Triplet Markov Chains in hidden signal restoration, SPIEs International Symposium on Remote Sensing, September 22-27, Crete, Greece, 2002.

[C48] S. Derrode and W. Pieczynski, SAR image segmentation using generalized Pairwise Markov Chains, SPIEs International Symposium on Remote Sensing, September 22-27, Crete, Greece, 2002.

[C47] W. Pieczynski, Modèles de Markov en imagerie, Conférence invitée, Actes des journées d’études « Le traitement d’image à l’aube du XXIème siècle », Paris, 28-29 mars 2002, pp. 125-136.

[C46] Y. Delignon , R. Fjrtoft  and W. Pieczynski, Compound distributions for radar images, Proceedings of 12 th Scandinavian Conference on Image Analysis, IAPR, June 11-14, 2001, Bergen, Norway.

[C45] R. Fjortoft, W. Pieczynski, and Y. Delignon, Generalized mixture estimation and unsupervised classification based on hidden Markov chains and hidden Markov random fields, Proceedings of 12 th Scandinavian Conference on Image Analysis, IAPR, June 11-14, 2001, Bergen, Norway.

[C44] R. Fjortoft, J.-M. Boucher, Y. Delignon, R. Garello, J.-M. Le Caillec, H. Maéesre, J.-M. Nicolas, W. Pieczynski, F. Tupin, M. Sigelle, Unsupervised Classification of Radar Images based on Hidden Markov Models and Generalised Mixture Estimation, Conference on SAR Image Analysis, Modelling and Techniques, European Symposium on Remote Sensing, 25-29 September 2000, Barcelona, Spain.

[C43] L. Fouque, A. Appriou, and W. Pieczynski, An Evidential Markovian Model for Data Fusion and Unsupervised Image Classification, Proceedings of 3rd International Conference on Information Fusion, FUSION 2000, Vol. 1, July 10th-13th, 2000, Paris, France, pp. TuB4-25 - TuB4-31.

[C42] W. Pieczynski, Pairwise Markov Chains and Bayesian Unsupervised Fusion, Proceedings of 3rd International Conference on Information Fusion, FUSION 2000, Vol. 1, July 10th-13th, 2000, Paris, France, pp. MoD4-24 - MoD4-31.

[C41] L. Fouque, A. Appriou, and W. Pieczynski, Multiresolution Hidden Markov Chain Model and Unsupervised Image Segmentation, Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI'2000), 2-4 April 2000, Austin, Texas, Etats-Unis, pp. 121-125.

[C40] W. Pieczynski, Unsupervised Dempster-Shafer fusion of dependent sensors, Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI'2000), 2-4 April 2000, Austin, Texas, Etats-Unis, pp. 247-251.

[C39] W. Pieczynski, A.-N. Tebbache, Pairwise Markov random fields and its application in textured images segmentation, Proceedings of IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI'2000), 2-4 April 2000, Austin, Texas, Etats-Unis, pp. 106-110.

[C38] L. Fouque, A. Appriou, W. Pieczynski, Modèle de Chaine de Markov Cachée Multirésolution et segmentation non supervisée d'images Actes du Congrès Reconaissance des Formes et Intelligence Artificielle, RFIA 2000, Paris, 1-3 Février 2000, pp. II267-II274.

[C37] W. Pieczynski, A.-N. Tebbache, Champs de Markov Aléatoires Couples et Segmentation des Images Texturées, Actes du Congrès Reconaissance des Formes et Intelligence Artificielle , RFIA 2000, Paris, 1-3 Février 2000, pp. II221-II228.

[C36] W. Pieczynski, Hidden evidential Markov trees and image segmentation, Proceedings of the IEEE International Conference on Image Processing (ICIP'99), 24-28 October 1999, Kobe, Japon.

[C35] L. Fouque, A.-N. Tebbache, et W. Pieczynski, Sur les segmentations statistiques non supervisées dans le contexte des mélanges généralisés, GRETSI'99, 13-17 septembre, Vannes, France, pp. 639-642, 1999.

[C34] E. Monfrini, T. Ledru, E. Vaie, et W. Pieczynski, Segmentation non supervisée d'images par arbres de Markov cachés, GRETSI 99, 13-17 septembre, Vannes, France, pp. 43-46, 1999.

[C33] A.Bendjebbour, W.Pieczynski, Unsupervised image segmentation using Dempster-Shafer fusion in a Markov fields contex, Proceedings First International Conference on Multisource-Multisensor Information Fusion (Fusion'98), Las Vegas, NA, 6-9 June 1998, pp. 595-600.

[C32] W. Pieczynski, J. Bouvrais, C. Michel, Unsupervised Bayesian fusion of correlated sensors, Proceedings First International Conference on Multisource-Multisensor Information Fusion (Fusion'98), Las Vegas, NA, 6-9 June 1998, pp. 794-801.

[C31] A. Bendjebbour, W. Pieczynski, Multisensor evidential Hidden Markov Fields and image segmentation, Proceedings Second IEEE International Conference on Intelligent Processing Systems (ICIPS'98), Gold Coast, Australia, 4-7 August 1998, pp. 188-192.

[C30] L. Amoura, W. Pieczynski, Hierarchical Markov fields and fuzzy image segmentation, Proceedings Second IEEE International Conference on Intelligent Processing Systems (ICIPS'98), Gold Coast, Australia, 4-7 August 1998, pp. 154-158.

[C29] N. Giordana and W. Pieczynski, Utilisation de la théorie de l'évidence pour la restauration de chaînes de Markov cachées multispectrales", GRETSI 97, 15-19 septembre, Grenoble, 1997.

[C28] A. Marzouki, Y. Delignon, W. Pieczynski, Segmentation d'images radar multispectrales utilisant une méthode d'estimation généralisée, Actes 1er Symposium International Processus de Traitement d'Images, Gammarth, Tunisia, September 1997.

[C27] N. Giordana, W. Pieczynski, Unsupervised restoration of generalized multisensor hidden Markov chains, Proceedings 8th European Signal Processing Conference (EUSIPCO'96), Trieste, Italy, September 1996.

[C26] N. Giordana, W. Pieczynski, Unsupervised segmentation of multisensor images using generalized hidden Markov chains, Proceedings International Conference on Image Processing (ICIP'96), Lausanne, Switzerland, September 1996.

[C25] A. Marzouki, Y. Delignon , and W. Pieczynski, Unsupervised statistical segmentation of multispectral SAR image using generalized mixture estimation, IGARSS-96, 27-31 mai 96, Lincoln, Nebraska, USA.

[C24] F. Salzenstein et W. Pieczynski, Choix automatique de la meilleurs méthode de segmentatin statistique non supervisée d'images, Quinzième Colloque GRETSI, Juan-Les-Pins, France, septembre 1995.

[C23] F. Salzenstein, W. Pieczynski, Unsupervised Bayesian segmentation using hidden fuzzy Markov Fields, Proceedings International Conference on Acoustics, Speech and Signal Processing (ICASSP'95), Detroit, MI, Vol. 4, pp. 2411-2413, May 1995.

[C22] Z. Kato, J. Zerubia, M. Berthod, W. Pieczynski, Unsupervised adaptive image segmentation, Proceedings International Conference on Acoustics, Speech and Signal Processing (ICASSP'95), Detroit, MI, Vol. 4, May 1995.

[C21] A. Marzouki, Y. Delignon, W. Pieczynski, Adaptive segmentation of SAR images, Proceedings OCEAN'94, Brest, France, September 1994.

[C20] A. Peng, W. Pieczynski, Adaptive unsupervised contextual statistical segmentation : Application on images of blood vessel, Proceedings SPIE International Symposium on Optics, Imaging and Instrumentation, San Diego, CA, July 1994.

[C19] H. Caillol, A. Hillion, et W. Pieczynski, Segmentation contextuelle non supervisée utilisant une modélisation statistique floue, Neuvième Congrès RFIA, Paris, France, janvier 1994.

[C18] B. Benmiloud, A. Peng, and W. Pieczynski, Estimation conditionnelle itérative dans les chaînes de Markov cachées et segmentation statistique non supervisée d'images, Quatorzième Colloque GRETSI 93, Juans-les-Pins, France, septembre 1993.

[C17] A. Peng, B. Benmiloud, W. Pieczynski, Adaptive unsupervised contextual Bayesian image segmentation, Proceedings IEEE Eight Workhop on Image and Multidimentional Signal Processing, Cannes, France, September 1993.

[C16] A. Marzouki, Y. Delignon, H. C. Quelle, and W. Pieczynski, Segmentation non supervisée d'images satellite utilisant un modèle hierarchique généralisé, Quatorzième Colloque GRETSI 93, Juans-les-Pins, France, septembre 1993.

[C15] S. Baziak, G. B. Bénié, J. M. Boucher, W. Pieczynski, and M. C. Vincent, Champs markoviens stationnaires et non stationnaires et recuit simulé: Application à la segmentation des images de télédétection, 16ème Symposium Canadien sur la Télédétection, 8ème Congrès de l'Association Québécoise de Télédétection, Sherbrooke, Quebec, juin 1993.

[C14] C. Banga, F. Ghorbel, W. Pieczynski, "Unsupervised Bayesian classifier applied to the segmentation of retina image", Proceedings 14th Annual International Conference of the IEEE Engineering in Medecine and Biology Society, Paris, October 1992.

[C13] O. Allagnat, J.M. Boucher, D.C. He, W. Pieczynski, "Hidden Markov fields and unsupervised segmentation of images", Proceedings 11th IAPR International Conference on Pattern Recognition (ICPR'92), Delft, The Netherlands, August 1992.

[C12] W. Pieczynski, "Parameter estimation in the case of hidden data", Proceedings 16th Biennal Symposium on Communications, Kingston, Canada, May 1992.

[C11] A. Peng, W. Pieczynski, "Edge detection by filtering and non-supervised Bayesian image segmentation" Proceedings 16th Biennal Symposium on ommunications, Kingston, Canada, May 1992.

[C10] H.C. Quelle, J.M. Boucher, W. Pieczynski, "Local parameter estimation and unsupervised segmentation of SAR images" Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS'92), Houston, TX, May 1992.

[C9] M. Emsalem, H. Caillol, P. Olivié, G. Carnat, W. Pieczynski, "Fast unsupervised statistical image segmentation" Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS'92), Houston, TX, May 1992.

[C8] H. Caillol, W. Pieczynski, "Fuzzy statistical unsupervised image segmentation", Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS'92), Houston, TX, May 1992.

[C7] W. Pieczynski, Statistical image segmentation, Machine Graphics and Vision, Vol. 1, No. 1/2 (Proceedings of GKiPO'92), pp. 261-268, 1992.

[C6] P. Masson, W. Pieczynski, "Segmentation contextuelle non supervisée des images SPOT", Proceedings RFIA'91, Villeurbanne, France, Novembre 1991.

[C5] B. Braathen, N. Marhic, P. Masson, and W. Pieczynski, Sur une nouvelle approche de segmentation bayesienne non supervisée d'images, Actes de GRETSI, Juan-les-Pins, France, septembre 1991.

[C4] H.C. Quelle, J.M. Boucher, W. Pieczynski, Unsupervised Bayesian classification of SAR images, Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS'91), Helsinki, Finland, June 1991.

[C3] N. Marhic, W. Pieczynski, "Estimation of mixture and unsupervised segmentation of images", Proceedings IEEE International Geoscience and Remote Sensing Symposium (IGARSS'91), Helsinki, Finland, June 1991.

[C2] P. Masson, W. Pieczynski, "Segmentation of SPOT images by contextual SEM", Proceedings EUSIPCO'90, Barcelone, Spain, October 1990.

[C1] Y. Rungsunseri, W. Pieczynski, C. Roux, Stratégie contextuelle et extraction de primitives pour la segmentation des images multispectrales, Actes de GRETSI, Juan-Les-Pins, France, juin 1989.

 

Past PhD students

 

[P20] Mohamed El Yazid Boudaren, Modèles graphiques évidentiels, thèse en cotutelle entre l’Université USTHB, Alger, Algérie, et l’Université Paris VI, Paris, soutenue à l’Université USTHB le 12 janvier 2014. Co-encadrée par Amar Aissani (USTHB), Emmanuel Monfrini (CITI, Telecom SudParis), et Wojciech Pieczynski (CITI, Telecom SudParis).

[P19] Selwa Rafi, Chaînes de Markov cachées et séparation non supervisée de sources, thèse de Telecom SudParis et de l’Université Pierre et Marie Curie (Paris 6), soutenue le 11 juin 2012. Encadrants: Marc Castella (CITI, Telecom SudParis) et Wojciech Pieczynski (CITI, Telecom SudParis).

 [P18] Noufel Abbassi, Chaînes de Markov triplets et filtrage optimal dans les systèmes à sauts, thèse de Telecom SudParis et de l’Université Pierre et Marie Curie (Paris 6), soutenue le 26 avril 2012. Encadrant: Wojciech Pieczynski (CITI, Telecom SudParis).

[P17] Mohamed Ben Mabrouk, Modèles de Markov triplets en restauration des signaux, thèse de Telecom SudParis et de l’Université Pierre et Marie Curie (Paris 6), soutenue le 26 avril 2011. Encadrant: Wojciech Pieczynski (CITI, Telecom SudParis).

[P16] Jérôme Lapuyade-Lahorgue, Sur diverses extensions des chaînes de Markov cachées avec application au traitement des signaux radar, thèse de l'Institut National des Télécommunications et de l’Université Pierre et Marie Curie (Paris 6), soutenue le 10 décembre 2008. Encadrants: Frédéric Barbaresco (Thales Air Systems) et Wojciech Pieczynski (CITI, Telecom SudParis).

[P15] Pierre Lanchantin, Chaînes de Markov triplets et segmentation non supervisée des signaux, thèse de l'Institut National des Télécommunications, soutenue le 5 décembre 2006. Encadrants : Fabien Salzenstein (Université de Strasbourg I) et Wojciech Pieczynski CITI, INT.

[P14] Dalila Benboudjema, Champs de Markov triplets et segmentation Bayésienne non supervisée d'images, thèse de l'Institut National des Télécommunications, soutenue le 12 décembre 2005. Encadrant: Wojciech Pieczynski CITI, INT.

[P13] Nicolas Brunel, Sur quelques extensions des chaînes de Markov cachées et couples. Application à la segmentation non supervisée des signaux radar, thèse de l'Université Paris VI, soutenue le 5 décembre 2005. Encadrants: Frédéric Barbaresco (Thales Air Defence), Paul Deheuvels (Paris VI, LSTA), et Wojciech Pieczynski CITI, INT.

[P12] Laurent Fouque, Sur une méthodologie générale de Fusion de Dempster-Shafer pour la classification Markovienne d'images multirésolution, Thèse de l'Université Paris VI, soutenue à l'Université Paris VI le 11 février 2002. Encadrants : Alain Appriour (ONERA) et Wojciech Pieczynski, CITI, INT.

[P11] Emmanuel Monfrini, Identifiabilité et Méthode des Moments dans les mélanges généralisés de distributions du système de Pearson, Thèse de l'Université Paris VI, soutenue à l'Université Paris VI le 4 janvier 2002. Encadrants : Daniel Pierre-Loti-Viaud (LSTA, Parsi VI) et Wojciech Pieczynski, CITI, INT.

[P10] Azzedine Bendjebbour, Segmentation d'images multisenseur par fusion de Dempster-Shafer dans un contexte markovien, Thèse de l'Université Paris VI, soutenue à l'Université Paris VI le 11 décembre 2000. Encadrants : Paul Deheuvels (LSTA, Parsi VI) et Wojciech Pieczynski, CITI, INT.

[P9] Lahlou Amoura, Modèle Markovien pyramidal flou et segmentation statistique d'images, Thèse de l'Université Paris VI, soutenue à l'Université Paris VI le 03 février 1998. Encadrants : Paul Deheuvels (LSTA, Parsi VI) et Wojciech Pieczynski, CITI, INT.

[P8] Nathalie Giordana, Segmentation non supervisée d'images multispectrales par chaînes de Markov cachées, Thèse de l'Université de Technologie de Compiègne soutenue à l'Institut National des Télécommunications le 23 décembre 1996. Encadrant : Wojciech Pieczynski, CITI, INT.

 [P7] Fabien Salzenstein, Modèles Markoviens Flous et Segmentation non Supervisée d'Images, thèse de l'Université de Rennes I soutenue à l'Institut National des Télécommunications le 19 décembre 1996. Encadrant : Wojciech Pieczynski, CITI, INT.

[P6] Abdelwaheb Marzouki, Segmentation statistique d'images radar, thèse de l'Université de Lille I soutenue à l'ENIC le 7. novembre 1996. Encadrants : Yves Delignon (ENIC, Lille) et Wojciech Pieczynski, CITI, INT.

[P5] Hélène Caillol, Segmentation statistique floue d'images, thèse de l'Université Paris VI soutenue à l'Université Paris VI le 23 janvier 1995. Encadrants : Alain Hillion, ENST de Bretagne et Wojciech Pieczynski, CITI, INT.

[P4] Nicole Marhic, Modélisation stochastique et classification des images satellite par des méthodes statistiques, thèse de l'Université de Rennes 1 soutenue à l'Ecole Nationale Supérieure des Télécommunications de Bretagne le 22 décembre 1994. Encadrants : Alain Hillion, ENST de Bretagne et Wojciech Pieczynski, CITI, INT.

[P3] Btissam Benmiloud, Chaînes de Markov cachées et segmentation statistique non supervisée de séquences d'images, thèse de l'Université Paris VII soutenue à l'Institut National des Télécommunications le 16 décembre 1994. Encadrants : Wojciech Pieczynski, CITI, INT.

[P2] Hans-Christoph Quelle, Segmentation Bayesienne non supervisée en imagerie radar, thèse de l'Université de Rennes 1 soutenue à l'Ecole Nationale Supérieure des Télécommunications de Bretagne le 11 février 1993. Encadrants : Jean-Marc Boucher, ENST de Bretagne et Wojciech Pieczynski, CITI, INT.

[P1] Anrong Peng, Segmentation statistique non supervisée d'images et détection des contours par filtrage, thèse de l'Université de Technologie de Compiègne soutenue à l'Institut National des Télécommunications le 12 novembre 1992. Encadrant : Wojciech Pieczynski, CITI, INT

 

 

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