Convolutional Neural Network for self mixing interferometry

Stéphane Barland; François Gustave

2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference
OSA Technical Digest (Optica Publishing Group, 2021),
paper jsiv_4_2

Convolutional Neural Network for self mixing interferometry

Stéphane Barland and François Gustave

European Quantum Electronics Conference 2021

Munich Germany
21–25 June 2021
ISBN: 978-1-6654-1876-8

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Learning in Imaging and Metrology II (jsiv_4)

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S. Barland and F. Gustave, "Convolutional Neural Network for self mixing interferometry," in 2021 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, OSA Technical Digest (Optica Publishing Group, 2021), paper jsiv_4_2.

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Abstract

We design and train a convolutional neural network to reconstruct the complex displacement of a target from a self-mixing interferometric signal. The networks prediction is robust against noise, alignment configurations and even across experimental setups.

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