Using deep learning to retrieve 3D geometrical characteristics of a particle field from 2D projected images: Application to multiphase flows

Autor: Dia, Kassem, Lamadie, Fabrice, Debayle, Johan

Publikováno v: ICPRS-12th International Conference on Pattern Recognition Systems
ICPRS-12th International Conference on Pattern Recognition Systems, École Nationale Supérieure des Mines de Saint-Étienne (France), Jun 2022, Saint-Étienne, France. pp.1 à 7, ⟨10.1109/ICPRS54038.2022.9854059⟩

International audience; The main part of recycling processes are carried out in chemical engineering reactors that involve multiphase flows with dense dispersed phase. In a study and modeling approach of these processes, the description and character

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::11e5f233c6ba7122b5a0f01f79ca10df
https://doi.org/10.1109/icprs54038.2022.9854059

Estimating the Parameters of a Stochastic Geometrical Model for Multiphase Flow Images Using Local Measures

Autor: Théodon, Léo, Eremina, Tatyana, Dia, Kassem, Lamadie, Fabrice, Pinoli, Jean-Charles, Debayle, Johan

Publikováno v: Image Analysis & Stereology
Image Analysis & Stereology, 2021, 40, pp.115 à 125
Image Analysis and Stereology, Vol 40, Iss 3, Pp 115-125 (2021)

International audience; This paper presents a new method for estimating the parameters of a stochastic geometric model for multiphase flow image processing using local measures. Local measures differ from global measures in that they are only based o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::66aee9164f56a7d7616626a24cfe1933
https://hal.science/hal-03542487/document