Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Robert Rapadamnaba"'
Publikováno v:
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, INRIA, In press, Volume 32-2019-2021, ⟨10.46298/arima.7160⟩
Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, INRIA, In press, Volume 32-2019-2021, ⟨10.46298/arima.7160⟩
The paper shows how to take advantage of a possible existing linear relationship in an optimization problem to address the issue of robust design and backward uncertainty propagation lowering as much as possible the computational effort.
L' arti
L' arti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::560e233bacdba67cf98fe08b22ae651c
https://arima.episciences.org/7160
https://arima.episciences.org/7160
Publikováno v:
International Journal for Numerical Methods in Biomedical Engineering
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2021
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2021
International audience; This paper shows how to obtain in addition to the standard deviations available after a data assimilation procedure based on the ensemble Kalman filter, an apportioning of the total uncertainty in the outputs of a patient-spec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49eb1d8f573222711d7fa4f206e30b0d
https://hal.archives-ouvertes.fr/hal-03216532/file/Main_document.pdf
https://hal.archives-ouvertes.fr/hal-03216532/file/Main_document.pdf
Publikováno v:
International Journal for Numerical Methods in Biomedical Engineering
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2020, ⟨10.1002/cnm.3325⟩
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2020, ⟨10.1002/cnm.3325⟩
International audience; This paper uses machine learning to enrich magnetic resonance angiography and magnetic resonance imaging acquisitions. A convolutional neural network is built and trained over a synthetic database linking geometrical parameter
Publikováno v:
International Journal for Numerical Methods in Biomedical Engineering
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2018, pp.1-24. ⟨10.1002/cnm.3170⟩
International Journal for Numerical Methods in Biomedical Engineering, John Wiley and Sons, 2018, pp.1-24. ⟨10.1002/cnm.3170⟩
International audience; Using a previously developed inversion platform for functional cerebral medical imaging with ensemble Kalman filters, this work analyzes the sensitivity of the results with respect to different parameters entering the physical