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Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data

Autor: Gangloff, Hugo, Morales, Katherine, Petetin, Yohan

Hidden Markov models are probabilistic graphical models based on hidden and observed random variables. They are popular to address classification tasks for time series applications such as part-of-speech tagging, image segmentation, genetic sequence

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9347a95752bef407ef49a25e9a1669ee
https://hal.science/hal-03584314

Unsupervised segmentation of nonstationary data using triplet Markov chains

Autor: Ahmed Habbouchi, Emmanuel Monfrini, Mohamed El Yazid Boudaren, Kadda Beghdad Bey, Wojciech Pieczynski

Publikováno v: Proceedings ICEIS 2017 : 19th International Conference on Enterprise Information Systems
ICEIS 2017 : 19th International Conference on Enterprise Information Systems
ICEIS 2017 : 19th International Conference on Enterprise Information Systems, Apr 2017, Porto, Portugal. pp.405-414, ⟨10.5220/0006276704050414⟩
ICEIS (1)
Scopus-Elsevier

International audience; An important issue in statistical image and signal segmentation consists in estimating the hidden variables of interest. For this purpose, various Bayesian estimation algorithms have been developed, particularly in the framewo

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ce2c74e20a8f427adf61e9c925d958e
https://hal.archives-ouvertes.fr/hal-01548177

Dempster-Shafer fusion of evidential pairwise Markov chains

Autor: Mohamed El Yazid Boudaren, Wojciech Pieczynski

Publikováno v: IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems, Institute of Electrical and Electronics Engineers, 2016, 24 (6), pp.1598-1610. ⟨10.1109/TFUZZ.2016.2543750⟩

International audience; Hidden Markov models have been extended in many directions, leading to pairwise Markov models, triplet Markov models, or discriminative random fields, all of which have been successfully applied in many fields covering signal

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95f1fe230340b7e445965fbda2f56b28
https://hal.archives-ouvertes.fr/hal-01426916

Phasic Triplet Markov Chains

Autor: Amar Aissani, Emmanuel Monfrini, Mohamed El Yazid Boudaren, Wojciech Pieczynski

Publikováno v: IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence, Institute of Electrical and Electronics Engineers, 2014, 36 (11), pp.2310-2316. ⟨10.1109/TPAMI.2014.2327974⟩

International audience; Hidden Markov chains have been shown to be inadequate for data modeling under some complex conditions. In this work, we address the problem of statistical modeling of phenomena involving two heterogeneous system states. Such p

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f87e84560a30752c4a33b770e6f4ac54
https://pubmed.ncbi.nlm.nih.gov/26353069