| Deep Learning architecture for topological optimized mechanical design generation with complex shape criterion W Almasri, D Bettebghor, F Ababsa, F Danglade, F Adjed International Conference on Industrial, Engineering and Other Applications …, 2021 | 10 | 2021 |
| Deep learning for additive manufacturing-driven topology optimization W Almasri, F Danglade, D Bettebghor, F Adjed, F Ababsa Procedia CIRP 109, 49-54, 2022 | 5 | 2022 |
| GMCAD: an original Synthetic Dataset of 2D Designs along their Geometrical and Mechanical Conditions W Almasri, D Bettebghor, F Adjed, F Ababsa, F Danglade Procedia Computer Science 200, 337-347, 2022 | 5 | 2022 |
| Geometrically-driven generation of mechanical designs through deep convolutional GANs W Almasri, D Bettebghor, F Adjed, F Danglade, F Ababsa Engineering Optimization 56 (1), 18-35, 2024 | 2 | 2024 |
| Shape related constraints aware generation of Mechanical Designs through Deep Convolutional GAN W Almasri, D Bettebghor, F Ababsa, F Danglade arXiv preprint arXiv:2010.11833, 2020 | 2 | 2020 |
| A data-driven topology optimization approach to handle geometrical manufacturing constraints in the earlier steps of the design phase W Almasri, F Danglade, D Bettebghor, F Adjed, F Ababsa Procedia CIRP 119, 377-383, 2023 | 1 | 2023 |
| Réseaux Antagonistes Génératifs 3d pour le design, l’optimisation et la validation numérique en fabrication additive W Almasri HESAM Université, 2023 | | 2023 |
Dimitri BettebghorResearch Scientist, Materials & Structures, ONERAVerified email at onera.fr
