| Full text | |
| Author(s): |
de Souza, Arthur Clini
;
Lanteri, Stephane
;
Hernandez-Figueroa, Hugo Enrique
;
Abbarchi, Marco
;
Grosso, David
;
Kerzabi, Badre
;
Elsawy, Mahmoud
Total Authors: 7
|
| Document type: | Journal article |
| Source: | MACHINE LEARNING IN PHOTONICS; v. 13017, p. 10-pg., 2024-01-01. |
| Abstract | |
The present work showcases an innovative optimization methodology based on deep learning that combines Multi-Valued Artificial Neural Networks and back-propagation optimization. The methodology addresses the inherent limitations of conventional approaches when employed in isolation. We applied the proposed methodology to design structural color filters that surpasses the sRGB gamut while preserving fabrication constraints. (AU) | |
| FAPESP's process: | 21/11380-5 - CPTEn - São Paulo Center for the Study of Energy Transition |
| Grantee: | Luiz Carlos Pereira da Silva |
| Support Opportunities: | Research Grants - Science Centers for Development |
| FAPESP's process: | 21/06506-0 - Strongly resonant all-dielectric metasurfaces based on quasi-dark and toroidal modes |
| Grantee: | Hugo Enrique Hernández Figueroa |
| Support Opportunities: | Regular Research Grants |