| Issue |
EPJ Web Conf.
Volume 266, 2022
EOS Annual Meeting (EOSAM 2022)
|
|
|---|---|---|
| Article Number | 13007 | |
| Number of page(s) | 2 | |
| Section | Topical Meeting (TOM) 13- Advances and Applications of Optics and Photonics | |
| DOI | https://doi.org/10.1051/epjconf/202226613007 | |
| Published online | 13 October 2022 | |
https://doi.org/10.1051/epjconf/202226613007
Convolutional neural network optimisation to enhance ESPI fringe visibility
QMatterPhotonics Research Group. Optics Area. Department of Applied hysics. Faculty of Physics / Faculty of Optics and Optometry. University of Santiago de Compostela. E-15782 Santiago de Compostela. Galicia. Spain
* Corresponding author: josemanuel.crespo.continas@rai.usc.es
Published online: 13 October 2022
The use of convolutional neuronal networks (CNN) for the treatment of interferometric fringes has been introduced in recent years. In this paper, we optimize and build a CNN model, based U-NET architecture, to maximize its performance processing electronic speckle interferometry fringes (ESPI).
© The Authors, published by EDP Sciences
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