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Publications

Affichage des publications 21 à 30 sur 315 au total

Sciences de l'ingénieur

A modified Constitutive Relation Error framework to learn nonlinear constitutive laws using physics-augmented Neural Networks

A novel data-driven approach to learn constitutive law with observable data is proposed in the context of structural health monitoring (SHM). Constitutive laws are represented by a physics-augmented neural network taking strain in input and free…

Antoine Benady, Ludovic Chamoin, Emmanuel Baranger

IACM Mechanistic Machine Learning and Digital Engineering for Computational Science Engineering and Technology. -

Sciences de l'ingénieur

A modified Constitutive Relation Error (mCRE) framework to learn nonlinear constitutive models from strain measurements with thermodynamics-consistent Neural Networks

The damage of mechanical structures is a permanent concern in engineering, related to issues of durability and safety. The theme is currently the subject of various research activities; a typical example is the ERC project DREAM-ON (2021-2026), in…

Antoine Benady, Emmanuel Baranger, Ludovic Chamoin

XI Conference on Adaptive Modeling and Simulation -

Sciences de l'ingénieur

Model updating with a Modified Dual Kalman Filter acting on distributed strain measurements

Following the advances in measurement technology and its vast availability, mechanical systems and structures are increasingly equipped with sensors to obtain continuous information regarding the system state. Coupled with robust numerical models,…

Sahar Farahbakhsh, Ludovic Chamoin, Martin Poncelet

XI International Conference on Adaptive Modeling and Simulation (ADMOS 2023) -

Traitement du signal et de l'image

Video joint denoising and demosaicing with recurrent CNNs

Le débruitage et le dématriçage sont deux composantes importantes de la chaîne de traitement des images et des vidéos. Tandis que traditionnellement, ces deux tâches ont largement été appliquées séparément, les approches actuelles basées sur les…

Valéry Dewil, Adrien Courtois, Mariano Rodríguez, Thibaud Ehret, Nicola Brandonisio, Denis Bujoreanu, Gabriele Facciolo, Pablo Arias

Winter Conference on Applications of Computer Vision (WACV) -

Analyse numérique

On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent

Bayesian methods to solve imaging inverse problems usually combine an explicit data likelihood function with a prior distribution that explicitly models expected properties of the solution. Many kinds of priors have been explored in the literature,…

Rémi Laumont, Valentin de Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, Marcelo Pereyra

Journal of Mathematical Imaging and Vision -

Sciences de l'ingénieur

Damage tracking using distributed optic fiber sensors in structures

La détection précoce de l’endommagement et le suivi de sa progression contribuent à améliorer la sécurité et la durabilité des structures. La capacité à modéliser et simuler ce phénomène, en complément de mesures, facilite le contrôle du système…

Sahar Farahbakhsh, Ludovic Chamoin, Martin Poncelet

25e Congrès Français de Mécanique -