Search Results - "Mémin, E."

Learning Variational Data Assimilation Models and Solvers by Fablet, R., Chapron, B., Drumetz, L., Mémin, E., Pannekoucke, O., Rousseau, F.

“…Data assimilation is a key component of operational systems and scientific studies for the understanding, modeling, forecasting and reconstruction of earth…”
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Large‐scale flows under location uncertainty: a consistent stochastic framework by Chapron, B., Dérian, P., Mémin, E., Resseguier, V.

“…Using a classical example, the Lorenz‐63 model, an original stochastic framework is applied to represent large‐scale geophysical flow dynamics. Rigorously…”
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New Trends in Ensemble Forecast Strategy: Uncertainty Quantification for Coarse-Grid Computational Fluid Dynamics by Resseguier, V., Li, L., Jouan, G., Dérian, P., Mémin, E., Chapron, B.

“…Numerical simulations of industrial and geophysical fluid flows cannot usually solve the exact Navier–Stokes equations. Accordingly, they encompass strong…”
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Fluid experimental flow estimation based on an optical-flow scheme by CORPETTI, T, HEITZ, D, ARROYO, G, MEMIN, E, SANTA-CRUZ, A

“…We present in this paper a novel approach dedicated to the measurement of velocity in fluid experimental flows through image sequences. Unlike most of the…”
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Hierarchical estimation of a dense deformation field for 3-D robust registration by Hellier, P., Barillot, C., Memin, E., Perez, P.

“…A new method for medical image registration is formulated as a minimization problem involving robust estimators. The authors propose an efficient hierarchical…”
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Inflow and initial conditions for direct numerical simulation based on adjoint data assimilation by Gronskis, A., Heitz, D., Mémin, E.

“…A method for generating inflow conditions for direct numerical simulations (DNS) of spatially-developing flows is presented. The proposed method is based on…”
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Geophysical flows under location uncertainty, Part II Quasi-geostrophy and efficient ensemble spreading by Resseguier, V., Mémin, E., Chapron, B.

“…Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly…”
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Geophysical flows under location uncertainty, Part I Random transport and general models by Resseguier, V., Mémin, E., Chapron, B.

“…A stochastic flow representation is considered with the Eulerian velocity decomposed between a smooth large scale component and a rough small-scale turbulent…”
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Stochastic representation of the Reynolds transport theorem: Revisiting large-scale modeling by Harouna, S. Kadri, Mémin, E.

“…•Large scale modeling based on stochastic Reynold transport theorem.•Generalization of the eddy viscosity assumption with turbophoresis advection term.•Subgrid…”
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Divergence-Free Wavelets and High Order Regularization by KADRI-HAROUNA, S, DERIAN, P, HEAS, P, MEMIN, E

“…Expanding on a wavelet basis the solution of an inverse problem provides several advantages. First of all, wavelet bases yield a natural and efficient…”
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Geophysical flows under location uncertainty, Part III SQG and frontal dynamics under strong turbulence conditions by Resseguier, V., Mémin, E., Chapron, B.

“…Models under location uncertainty are derived assuming that a component of the velocity is uncorrelated in time. The material derivative is accordingly…”
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Strong and weak constraint variational assimilations for reduced order fluid flow modeling by Artana, G., Cammilleri, A., Carlier, J., Mémin, E.

“…In this work we propose and evaluate two variational data assimilation techniques for the estimation of low order surrogate experimental dynamical models for…”
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Optical flow for image-based river velocity estimation by Khalid, M., Pénard, L., Mémin, E.

“…We present a novel motion estimation technique for image-based river velocimetry. It is based on the so-called optical flow, which is a well developed method…”
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Mean wind flow reconstruction of a high-rise building based on variational data assimilation using sparse pressure measurements by Ben Ali, M.Y., Tissot, G., Aguinaga, S., Heitz, D., Mémin, E.

“…The paper investigates the applicability of the variational data assimilation approach to reconstruct three-dimensional wind flows around a high-rise building…”
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Dense estimation of fluid flows by Corpetti, T., Memin, E., Perez, P.

“…In this paper, we address the problem of estimating and analyzing the motion of fluids in image sequences. Due to the great deal of spatial and temporal…”
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Monte Carlo fixed-lag smoothing in state-space models by Cuzol, A., Mémin, E.

“…This paper presents an algorithm for Monte Carlo fixed-lag smoothing in state-space models defined by a diffusion process observed through noisy discrete-time…”
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Three-Dimensional Motion Estimation of Atmospheric Layers From Image Sequences by Heas, P., Memin, E.

“…In this paper, we address the problem of estimating 3-D motions of a stratified atmosphere from satellite image sequences. The analysis of 3-D atmospheric…”
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Dense estimation and object-based segmentation of the optical flow with robust techniques by Memin, E., Perez, P.

“…We address the issue of recovering and segmenting the apparent velocity field in sequences of images. As for motion estimation, we minimize an objective…”
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A Stochastic Filtering Technique for Fluid Flow Velocity Fields Tracking by Cuzol, A., Memin, E.

“…In this paper, we present a method for the temporal tracking of fluid flow velocity fields. The technique we propose is formalized within a sequential Bayesian…”
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Stochastic Level Set Dynamics to Track Closed Curves Through Image Data by Avenel, C., Mémin, E., Pérez, P.

“…We introduce a stochastic filtering technique for the tracking of closed curves from image sequence. For that purpose, we design a continuous-time dynamics…”
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