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
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
