Semi-supervised deep learning model for efficient computation of optical properties of suspended-core fibers

HIGHLIGHTS

• who: Gao Wang and collaborators from the State Key Laboratory of Dynamic Measurement Technology, North University of China have published the paper: Semi-Supervised Deep Learning Model for Efficient Computation of Optical Properties of Suspended-Core Fibers, in the Journal: Sensors 2022, 22, 6751. of /2022/
• what: Taking SCF`s three key optical properties (effective mode area nonlinear coefficient and dispersion) as examples the authors demonstrate that satisfactory computational results can be obtained based on small-scale training data. The model consists of a GAN, which is used to augment the limited a priori data . . .
  

   

  

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