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Etienne Mémin

Showing results (1-10 of 9) with videos related to

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IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|July 28, 2011
Stochastic uncertainty models for the luminance consistency assumptionThomas Corpetti, Etienne Mémin
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 16, 2009
A stochastic filtering technique for fluid flow velocity fields trackingAnne Cuzol, Etienne Mémin
Information Processing in Medical Imaging : Proceedings of the ... Conference|March 16, 2007
A novel parametric method for non-rigid image registrationAnne Cuzol, Pierre Hellier, Etienne Mémin
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|December 15, 2011
Bayesian inference of models and hyperparameters for robust optical-flow estimationPatrick Héas, Cédric Herzet, Etienne Mémin
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|January 14, 2005
Conditional filters for image sequence-based tracking--application to point trackingElise Arnaud, Etienne Mémin, Bruno Cernuschi-Frías
Physical Review. E|July 24, 2019
Stochastic flow approach to model the mean velocity profile of wall-bounded flowsBenoît Pinier, Etienne Mémin, Sylvain Laizet, et al.
Physical Review. E|April 16, 2022
Eigenvalues of autocovariance matrix: A practical method to identify the Koopman eigenfrequenciesYicun Zhen, Bertrand Chapron, Etienne Mémin, et al.
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|February 2, 2008
One-dimensional dense disparity estimation for three-dimensional reconstructionLionel Oisel, Etienne Mémin, Luce Morin, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 20, 2013
Bayesian estimation of turbulent motionPatrick Héas, Cédric Herzet, Etienne Mémin, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|July 28, 2011
Stochastic uncertainty models for the luminance consistency assumptionThomas Corpetti, Etienne Mémin
IEEE Transactions on Pattern Analysis and Machine Intelligence|May 16, 2009
A stochastic filtering technique for fluid flow velocity fields trackingAnne Cuzol, Etienne Mémin
Information Processing in Medical Imaging : Proceedings of the ... Conference|March 16, 2007
A novel parametric method for non-rigid image registrationAnne Cuzol, Pierre Hellier, Etienne Mémin
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|December 15, 2011
Bayesian inference of models and hyperparameters for robust optical-flow estimationPatrick Héas, Cédric Herzet, Etienne Mémin
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|January 14, 2005
Conditional filters for image sequence-based tracking--application to point trackingElise Arnaud, Etienne Mémin, Bruno Cernuschi-Frías
Physical Review. E|July 24, 2019
Stochastic flow approach to model the mean velocity profile of wall-bounded flowsBenoît Pinier, Etienne Mémin, Sylvain Laizet, et al.
Physical Review. E|April 16, 2022
Eigenvalues of autocovariance matrix: A practical method to identify the Koopman eigenfrequenciesYicun Zhen, Bertrand Chapron, Etienne Mémin, et al.
IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society|February 2, 2008
One-dimensional dense disparity estimation for three-dimensional reconstructionLionel Oisel, Etienne Mémin, Luce Morin, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|April 20, 2013
Bayesian estimation of turbulent motionPatrick Héas, Cédric Herzet, Etienne Mémin, et al.
Pageof 1