Deep-learning algorithms for imperfection-resilient Fourier-transform spectroscopy in silicon-Reference-Cited by-同舟云学术

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Deep-learning algorithms for imperfection-resilient Fourier-transform spectroscopy in silicon

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 17th International Conference on Group IV Photonics (GFP)
language:
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Author:

Mokeddem Zindine,Melati Daniele,Gonzalez-Andrade David,Duong Dinh Thi Thuy,Montesinos-Ballester Miguel,Cassan Eric,Marris-Morini Delphine,Grinberg Yuri,Cheben Pavel,Xu Dan-Xia,Schmid Jens,Vivien Laurent,Velasco Aitor V.,Alonso-Ramos Carlos

Funder

Agence Nationale de la Recherche

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9673705/9673807/09673932.pdf?arnumber=9673932

Reference7 articles.

1. Analysis of Tunable Flat-Top Bandpass Filters Based on Graphene

2. High-resolution compact on-chip spectrometer based on an Echelle grating with densely packed waveguide array;ma;IEEE Photonics J,2018

3. On-chip Fourier-transform spectrometers and machine learning: a new route to smart photonic sensors

4. High-resolution Fourier-transform spectrometer chip with microphotonic silicon spiral waveguides

5. Object Recognition with Gradient-Based Learning

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