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20172026
most citedLearning to decompose the modes in few-mode fibers with deep convolutional neural network

169 citations · 306 across the 11 of their papers we have counts for

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Showing 2019Show all

2 papers · 1 filter

physics.optics2019

Preliminary study on the modal decomposition of Hermite Gaussian beams via deep learning

Yi An, Tianyue Hou, Jun Li +4

The Hermite-Gaussian (HG) modes make up a complete and orthonormal basis, which have been extensively used to describe optical fields. Here, we demonstrate, for the first time to o…

eess.IV2019★ 31 cited

Deep learning enabled superfast and accurate M^2 evaluation for fiber beams

Yi An, Jun Li, Liangjin Huang +3

We introduce deep learning technique to predict the beam propagation factor M^2 of the laser beams emitting from few-mode fiber for the first time, to the best of our knowledge. Th…