Wojciech Pieczynski

Orcid: 0000-0002-1371-2627

According to our database1, Wojciech Pieczynski authored at least 108 papers between 1992 and 2023.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2023
Non-stationary data segmentation with hidden evidential semi-Markov chains.
Int. J. Approx. Reason., November, 2023

A new hybrid model of convolutional neural networks and hidden Markov chains for image classification.
Neural Comput. Appl., August, 2023

Traffic state prediction using conditionally Gaussian observed Markov fuzzy switching model.
J. Intell. Transp. Syst., July, 2023

Equivalence between LC-CRF and HMM, and Discriminative Computing of HMM-Based MPM and MAP.
Algorithms, March, 2023

Linear chain conditional random fields, hidden Markov models, and related classifiers.
CoRR, 2023

2022
Reduced-Dimension Filtering in Triplet Markov Models.
IEEE Trans. Autom. Control., 2022

Kernel smoothing classification of multiattribute data in the belief function framework: Application to multichannel image segmentation.
Multim. Tools Appl., 2022

Deriving discriminative classifiers from generative models.
CoRR, 2022

Improving Usual Naive Bayes Classifier Performances with Neural Naive Bayes based Models.
Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods, 2022

On Equivalence between Linear-chain Conditional Random Fields and Hidden Markov Chains.
Proceedings of the 14th International Conference on Agents and Artificial Intelligence, 2022

2021
Toward a Cost-Effective Motorway Traffic State Estimation From Sparse Speed and GPS Data.
IEEE Access, 2021

One Convolutional Layer Model For Parking Occupancy Detection.
Proceedings of the IEEE International Smart Cities Conference, 2021

Using the Naive Bayes as a discriminative model.
Proceedings of the ICMLC 2021: 13th International Conference on Machine Learning and Computing, 2021

Introducing the Hidden Neural Markov Chain Framework.
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021

Fast Image Segmentation with Contextual Scan and Markov Chains.
Proceedings of the 29th European Signal Processing Conference, 2021

Highly Fast Text Segmentation With Pairwise Markov Chains.
Proceedings of the 6th IEEE Congress on Information Science and Technology, 2021

2020
Filtering in Gaussian Linear Systems With Fuzzy Switches.
IEEE Trans. Fuzzy Syst., 2020

Suboptimal Kalman Filtering in Triplet Markov Models Using Model Order Reduction.
IEEE Signal Process. Lett., 2020

Semi-supervised optimal recursive filtering and smoothing in non-Gaussian Markov switching models.
Signal Process., 2020

State estimation in pairwise Markov models with improved robustness using unbiased FIR filtering.
Signal Process., 2020

Using the Naive Bayes as a discriminative classifier.
CoRR, 2020

Hidden Markov Chains, Entropic Forward-Backward, and Part-Of-Speech Tagging.
CoRR, 2020

Fast Segmentation of Markov Random Fields Corrupted by Correlated Noise.
Proceedings of the Advances in Computing Systems and Applications, 2020

2019
Parameter Estimation in Switching Markov Systems and Unsupervised Smoothing.
IEEE Trans. Autom. Control., 2019

Lower Limb Locomotion Activity Recognition of Healthy Individuals Using Semi-Markov Model and Single Wearable Inertial Sensor.
Sensors, 2019

An adaptive and on-line IMU-based locomotion activity classification method using a triplet Markov model.
Neurocomputing, 2019

2018
Assessing the segmentation performance of pairwise and triplet Markov models.
Signal Process., 2018

Unsupervised segmentation of hidden Markov fields corrupted by correlated non-Gaussian noise.
Int. J. Approx. Reason., 2018

Free-Walking 3D Pedestrian Large Trajectory Reconstruction from IMU Sensors.
Proceedings of the 26th European Signal Processing Conference, 2018

2017
Fast Filtering in Switching Approximations of Nonlinear Markov Systems With Applications to Stochastic Volatility.
IEEE Trans. Autom. Control., 2017

Fast smoothing in switching approximations of non-linear and non-Gaussian models.
Comput. Stat. Data Anal., 2017

Triplet Markov Chains Based- Estimation of Nonstationary Latent Variables Hidden with Independent Noise.
Proceedings of the Enterprise Information Systems - 19th International Conference, 2017

Unsupervised Segmentation of Nonstationary Data using Triplet Markov Chains.
Proceedings of the ICEIS 2017, 2017

Unsupervised learning of asymmetric high-order autoregressive stochastic volatility model.
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Pairwise Markov models for stock index forecasting.
Proceedings of the 25th European Signal Processing Conference, 2017

2016
Dempster-Shafer Fusion of Evidential Pairwise Markov Chains.
IEEE Trans. Fuzzy Syst., 2016

Unified Representation of Sets of Heterogeneous Markov Transition Matrices.
IEEE Trans. Fuzzy Syst., 2016

Unsupervised Segmentation of Markov Random Fields Corrupted by Nonstationary Noise.
IEEE Signal Process. Lett., 2016

Unsupervised classification using hidden Markov chain with unknown noise copulas and margins.
Signal Process., 2016

Unsupervised Segmentation of SAR Images Using Gaussian Mixture-Hidden Evidential Markov Fields.
IEEE Geosci. Remote. Sens. Lett., 2016

Dempster-Shafer fusion of evidential pairwise Markov fields.
Int. J. Approx. Reason., 2016

Fast filtering with new sparse transition Markov chains.
Proceedings of the IEEE Statistical Signal Processing Workshop, 2016

An Exact Smoother in a Fuzzy Jump Markov Switching Model.
Proceedings of the Representations, Analysis and Recognition of Shape and Motion from Imaging Data, 2016

Parameter estimation in conditionally Gaussian pairwise Markov switching models and unsupervised smoothing.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Unsupervised learning of Markov-switching stochastic volatility with an application to market data.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

Evidential Correlated Gaussian Mixture Markov Model for Pixel Labeling Problem.
Proceedings of the Belief Functions: Theory and Applications, 2016

2015
Optimal Filter Approximations in Conditionally Gaussian Pairwise Markov Switching Models.
IEEE Trans. Autom. Control., 2015

Exact fast smoothing in switching models with application to stochastic volatility.
Proceedings of the 23rd European Signal Processing Conference, 2015

2014
Filtrage statistique optimal rapide dans des systèmes linéaires à sauts non stationnaires.
Traitement du Signal, 2014

Subsampling-based HMC parameter estimation with application to large datasets classification.
Signal Image Video Process., 2014

Phasic Triplet Markov Chains.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Fast filter in non-linear systems with application to stochastic volatility model.
Proceedings of the 22nd European Signal Processing Conference, 2014

2013
Exact Fast Computation of Optimal Filter in Gaussian Switching Linear Systems.
IEEE Signal Process. Lett., 2013

Separation of instantaneous mixtures of a particular set of dependent sources using classical ICA methods.
EURASIP J. Adv. Signal Process., 2013

Unsupervised data classification using pairwise Markov chains with automatic copulas selection.
Comput. Stat. Data Anal., 2013

Challenging eye segmentation using Triplet Markov spatial models.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
Segmentation d'images par modèle de mélange conjoint non gaussien.
Traitement du Signal, 2012

Unsupervised Segmentation of Random Discrete Data Hidden With Switching Noise Distributions.
IEEE Signal Process. Lett., 2012

Unsupervised segmentation of hidden semi-Markov non-stationary chains.
Signal Process., 2012

Dempster-Shafer fusion of multisensor signals in nonstationary Markovian context.
EURASIP J. Adv. Signal Process., 2012

Unsupervised segmentation of nonstationary pairwise Markov Chains using evidential priors.
Proceedings of the 20th European Signal Processing Conference, 2012

2011
Unsupervised segmentation of randomly switching data hidden with non-Gaussian correlated noise.
Signal Process., 2011

Unsupervised segmentation of switching pairwise Markov chains.
Proceedings of the 7th International Symposium on Image and Signal Processing and Analysis, 2011

An extension of the ICA model using latent variables.
Proceedings of the IEEE International Conference on Acoustics, 2011

Unsupervised restoration in Gaussian Pairwise Mixture Model.
Proceedings of the 19th European Signal Processing Conference, 2011

2010
Modeling and Unsupervised Classification of Multivariate Hidden Markov Chains With Copulas.
IEEE Trans. Autom. Control., 2010

Unsupervised segmentation of new semi-Markov chains hidden with long dependence noise.
Signal Process., 2010

2008
Unsupervised segmentation of triplet Markov chains hidden with long-memory noise.
Signal Process., 2008

Fusion of textural statistics using a similarity measure: application to texture recognition and segmentation.
Pattern Anal. Appl., 2008

2007
Unsupervised Statistical Segmentation of Nonstationary Images Using Triplet Markov Fields.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

Multisensor triplet Markov chains and theory of evidence.
Int. J. Approx. Reason., 2007

Unsupervised segmentation of SAR images using Triplet Markov fields and fisher noise distributions.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2007

2006
Kalman filtering in pairwise Markov trees.
Signal Process., 2006

Multisensor triplet Markov fields and theory of evidence.
Image Vis. Comput., 2006

Copula-based Stochastic Kernels for Abrupt Change Detection.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2006

Contextual Estimation Of Hidden Markov Chains With Application To Image Segmentation.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Unsupervised Segmentation Of Non Stationary Images With Non Gaussian Correlated Noise Using Triplet Markov Fields And The Pearson System.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

2005
Unsupervised restoration of hidden nonstationary Markov chains using evidential priors.
IEEE Trans. Signal Process., 2005

Unsupervised signal restoration using hidden Markov chains with copulas.
Signal Process., 2005

Unsupervised image segmentation using triplet Markov fields.
Comput. Vis. Image Underst., 2005

Segmenting non stationary images with triplet Markov fields.
Proceedings of the 2005 International Conference on Image Processing, 2005

Copulas in Vectorial Hidden Markov Chains for Multicomponent Image Segmentation.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

2004
Signal and image segmentation using pairwise Markov chains.
IEEE Trans. Signal Process., 2004

2003
Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields.
IEEE Trans. Geosci. Remote. Sens., 2003

Pairwise Markov Chains.
IEEE Trans. Pattern Anal. Mach. Intell., 2003

Multiscale oil slick segmentation with Markov chain model.
Proceedings of the 2003 IEEE International Geoscience and Remote Sensing Symposium, 2003

Unsupervised multicomponent image segmentation combining a vectorial HMC model and ICA.
Proceedings of the 2003 International Conference on Image Processing, 2003

Kalman filtering using pairwise Gaussian models.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

Particle filtering with pairwise Markov processes.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003

2002
Modeling non-Rayleigh speckle distribution in SAR images.
IEEE Trans. Geosci. Remote. Sens., 2002

2001
Multisensor image segmentation using Dempster-Shafer fusion in Markov fields context.
IEEE Trans. Geosci. Remote. Sens., 2001

2000
Estimation of generalized mixture in the case of correlated sensors.
IEEE Trans. Image Process., 2000

Pairwise Markov Random Fields and its Application in Textured Images Segmentation.
Proceedings of the 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000

Unsupervised Dempster-Shafer Fusion of Dependent Sensors.
Proceedings of the 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000

Multiresolution Hidden Markov Chain Model and Unsupervised Image Segmentation.
Proceedings of the 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000

1999
Hidden Evidential Markov Trees and Image Segmentation.
Proceedings of the 1999 International Conference on Image Processing, 1999

1997
Estimation of generalized mixtures and its application in image segmentation.
IEEE Trans. Image Process., 1997

Estimation of fuzzy Gaussian mixture and unsupervised statistical image segmentation.
IEEE Trans. Image Process., 1997

Estimation of Generalized Multisensor Hidden Markov Chains and Unsupervised Image Segmentation.
IEEE Trans. Pattern Anal. Mach. Intell., 1997

Parameter Estimation in Hidden Fuzzy Markov Random Fields and Image Segmentation.
CVGIP Graph. Model. Image Process., 1997

1996
Unsupervised segmentation of multisensor images using generalized hidden Markov chains.
Proceedings of the Proceedings 1996 International Conference on Image Processing, 1996

Unsupervised restoration of generalized multisensor Hidden Markov Chains.
Proceedings of the 8th European Signal Processing Conference, 1996

1995
Adaptive Mixture Estimation and Unsupervised Local Bayesian Image Segmentation.
CVGIP Graph. Model. Image Process., 1995

Unsupervised Bayesian segmentation using hidden Markovian fields.
Proceedings of the 1995 International Conference on Acoustics, 1995

Unsupervised adaptive image segmentation.
Proceedings of the 1995 International Conference on Acoustics, 1995

1993
SEM algorithm and unsupervised statistical segmentation of satellite images.
IEEE Trans. Geosci. Remote. Sens., 1993

Fuzzy random fields and unsupervised image segmentation.
IEEE Trans. Geosci. Remote. Sens., 1993

1992
Hidden Markov fields and unsupervised segmentation of images.
Proceedings of the 11th IAPR International Conference on Pattern Recognition, 1992


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