Zobrazeno 1 - 10
of 191
pro vyhledávání: '"algorithme EM"'
Autor:
Obakrim, Said
Publikováno v:
Data Structures and Algorithms [cs.DS]. Université Rennes 1, 2022. English. ⟨NNT : 2022REN1S060⟩
Ocean wave climate has a significant impact on human activities, and its understanding is socioeconomically and environmentally important. In this thesis, we are interested in characterizing sea state parameters such as significant wave height (Hs) u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______2755::91770bc38d6bfc0d71380e6c0dfceded
https://theses.hal.science/tel-03952800/file/OBAKRIM_Said.pdf
https://theses.hal.science/tel-03952800/file/OBAKRIM_Said.pdf
Publikováno v:
RFIAP 2022-Reconnaissance des Formes, Image, Apprentissage et Perception
RFIAP 2022-Reconnaissance des Formes, Image, Apprentissage et Perception, Jul 2022, Vannes, France. pp.1-10
RFIAP 2022-Reconnaissance des Formes, Image, Apprentissage et Perception, Jul 2022, Vannes, France. pp.1-10
This paper presents a CNN-based fully unsupervised method for motion segmentation from optical flow. We assume that the input optical flow can be represented as a piecewise set of parametric motion models, typically, affine or quadratic motion models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::dde7aa5b28bfb32fdcbbdd2b7ffa3dbf
https://hal.inria.fr/hal-03926935
https://hal.inria.fr/hal-03926935
Autor:
Antonazzo, Filippo
Publikováno v:
Data Structures and Algorithms [cs.DS]. Université de Lille, 2022. English. ⟨NNT : 2022ULILB015⟩
Statistics [math.ST]. Université de Lille, 2022. English. ⟨NNT : ⟩
Statistics [math.ST]. Université de Lille, 2022. English. ⟨NNT : ⟩
Clustering reveals all its interest when the data set size considerably increases, since there is the opportunity to discover tiny but possibly high value clusters, which can not be detected with moderate sample sizes. However, the clustering of such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::3fe75bf7693d2ff1066ed2d94bec5b7a
https://theses.hal.science/tel-03846222
https://theses.hal.science/tel-03846222
Autor:
Martel, Yannick
L’algorithme EM (Dempster et al., 1977) permet de construire une séquence d’estimateurs qui converge vers l’estimateur de vraisemblance maximale pour des modèles à données manquantes pour lesquels l’estimateur du maximum de vraisemblance
Externí odkaz:
http://hdl.handle.net/1866/25477
Publikováno v:
Congrès Lambda Mu 22 « Les risques au cœur des transitions » (e-congrès)-22e Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Institut pour la Maîtrise des Risques
Congrès Lambda Mu 22 « Les risques au cœur des transitions » (e-congrès)-22e Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Institut pour la Maîtrise des Risques, Oct 2020, Le Havre (e-congrès), France
Congrès Lambda Mu 22 « Les risques au cœur des transitions » (e-congrès)-22e Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Institut pour la Maîtrise des Risques, Oct 2020, Le Havre (e-congrès), France
International audience; Cette communication introduit une approche originale de la maintenance des lignes de marquage. Une classification ascendante hiérarchique segmente la ligne en zones stratégiques et un algorithme EM estime un modèle de duré
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9ee063a76bf6600e26ccb10ad61e6cd5
https://hal.archives-ouvertes.fr/hal-03462949/file/LM22_COM_FULL_482846_Maxime_Redondin_20200717_306017.pdf
https://hal.archives-ouvertes.fr/hal-03462949/file/LM22_COM_FULL_482846_Maxime_Redondin_20200717_306017.pdf
Autor:
Thomas Lartigue
Publikováno v:
Statistics [math.ST]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAX034⟩
HAL
HAL
Describing the co-variations between several observed random variables is a delicate problem. Dependency networks are popular tools that depict the relations between variables through the presence or absence of edges between the nodes of a graph. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::f240d438fd76e16d6ba994e6d5528115
https://tel.archives-ouvertes.fr/tel-02981007
https://tel.archives-ouvertes.fr/tel-02981007
Autor:
Lartigue, Thomas
Publikováno v:
Statistics [math.ST]. Institut Polytechnique de Paris, 2020. English. ⟨NNT : 2020IPPAX034⟩
Describing the co-variations between several observed random variables is a delicate problem. Dependency networks are popular tools that depict the relations between variables through the presence or absence of edges between the nodes of a graph. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::28c733da90f2bebd7923b5e486322cec
https://tel.archives-ouvertes.fr/tel-02981007
https://tel.archives-ouvertes.fr/tel-02981007
Autor:
Greciet, Florine
Publikováno v:
Mathématiques [math]. Université de Lorraine, 2020. Français. ⟨NNT : 2020LORR0004⟩
An aircraft engine is made up of several families of materials that undergo multiple degradation mechanisms from their manufacture but also during their flight cycle (take-off, landing, pressurization, pilot manoeuvring,...) or during its rest on the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::0a1171dac94f26d89c7b4d941d4f490c
https://hal.univ-lorraine.fr/tel-02510850/file/DDOC_T_2020_0004_GRECIET.pdf
https://hal.univ-lorraine.fr/tel-02510850/file/DDOC_T_2020_0004_GRECIET.pdf
Publikováno v:
Computational Statistics and Data Analysis
Computational Statistics and Data Analysis, Elsevier, 2017, 111, pp.27-47. ⟨10.1016/j.csda.2017.01.006⟩
Computational Statistics and Data Analysis, Elsevier, 2017, 111, pp.27-47. ⟨10.1016/j.csda.2017.01.006⟩
International audience; A novel approach to perform unsupervised sequential learning for functional data is proposed. The goal is to extract reference shapes (referred to as templates) from noisy, deformed and censored realizations of curves and imag
Autor:
Huynh, Bao-Tuyen
Publikováno v:
Statistics [math.ST]. LMNO Lab CNRS, UMR 6139, University of Caen, 2019. English
This thesis deals with the problem of modeling and estimation of high-dimensional MoE models, towards effective density estimation, prediction and clustering of such heterogeneous and high-dimensional data. We propose new strategies based on regulari
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4d25932790239651f63e6db2122507d7
https://hal.archives-ouvertes.fr/tel-02397752
https://hal.archives-ouvertes.fr/tel-02397752