Photoelastic Dispersion Coefficient by Holographic Reconstruction with Neural Networks and the Fresnel Method

Autor(es)

Prado, Felipe Maia ; Miho de Souza, Pedro Henrique ; da Silva, Sidney Leal ; Wetter, Niklaus Ursus ; IEEE

• Tipo de documento: Artigo Científico
• Fonte: 2023 INTERNATIONAL CONFERENCE ON OPTICAL MEMS AND NANOPHOTONICS, OMN AND SBFOTON INTERNATIONAL OPTICS AND PHOTONICS CONFERENCE, SBFOTON IOPC; v. N/A, p. 2-pg., 2023-01-01.

Resumo

Here we report the characterization of the photoelastic dispersion coefficient using digital holography with two distinct reconstruction methods: one based on the Fresnel method and the other utilizing convolutional neural networks (CNN). The CNN was trained with reconstruction from the Fresnel method and was able to provide reconstructions with an average Mean Squared Error of 0.006. (AU)

• Processo FAPESP: 22/15276-0 - Redes Neurais Ópticas com Novas Funções de Ativação Não Lineares para Recuperação de Fases Aplicadas à Holografia Digital
• Beneficiário: Felipe Maia Prado
• Modalidade de apoio: Bolsas no Brasil - Doutorado