Deep learning characterizes optical pulses using speckle patterns at the end of multimode fibers

Scilight ◽  
2020 ◽  
Vol 2020 (38) ◽  
pp. 381102
Author(s):  
Aili McConnon
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Changyan Zhu ◽  
Eng Aik Chan ◽  
You Wang ◽  
Weina Peng ◽  
Ruixiang Guo ◽  
...  

AbstractMultimode fibers (MMFs) have the potential to carry complex images for endoscopy and related applications, but decoding the complex speckle patterns produced by mode-mixing and modal dispersion in MMFs is a serious challenge. Several groups have recently shown that convolutional neural networks (CNNs) can be trained to perform high-fidelity MMF image reconstruction. We find that a considerably simpler neural network architecture, the single hidden layer dense neural network, performs at least as well as previously-used CNNs in terms of image reconstruction fidelity, and is superior in terms of training time and computing resources required. The trained networks can accurately reconstruct MMF images collected over a week after the cessation of the training set, with the dense network performing as well as the CNN over the entire period.


2021 ◽  
Vol 13 (1) ◽  
pp. 1-7
Author(s):  
Jinhua Yan ◽  
Ming Jin ◽  
Zhousu Xu ◽  
Lei Chen ◽  
Ziheng Zhu ◽  
...  

2019 ◽  
Vol 27 (15) ◽  
pp. 20241 ◽  
Author(s):  
Pengfei Fan ◽  
Tianrui Zhao ◽  
Lei Su

Author(s):  
Babak Rahmani ◽  
Damien Loterie ◽  
Georgia Konstantinou ◽  
Demetri Psaltis ◽  
Christophe Moser

2021 ◽  
Vol 3 (1) ◽  
pp. 015003
Author(s):  
Jun Zhao ◽  
Xuanxuan Ji ◽  
Minghai Zhang ◽  
Xiaoyan Wang ◽  
Ziyang Chen ◽  
...  

2015 ◽  
Author(s):  
M. Lomer ◽  
L. Rodriguez-Cobo ◽  
F. Madruga ◽  
J. M. Lopez-Higuera

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