CoreNet

Phase encode deep neural network for complex wavefront shaping through multi-core fibers

Updated March 2023

Structure of the phase encoder deep neural network (CoreNet)

Table of Contents

• General Info
• Download DNN
• How to use
• Contact

General Information

• The Matlab code can generate holograms for complex wavefront shaping through a multi-core fiber bundle.
• The deep neural network is pre-trained with MNIST dataset and can be used directly.
• You can read our paper for detailed information [1]. Please cite our paper if you used this code for publication.
• [1] Sun J, Wu J, Koukourakis N, et al. Real-time complex light field generation through a multi-core fiber with deep learning[J]. Scientific reports, 2022, 12(1): 1-10. https://www.nature.com/articles/s41598-022-11803-7

Download DNN

• The pre-trained CoreNet can be downloaded at
• https://drive.google.com/file/d/1itj4jtysSo2rxrFa4OSSTneZayGFLq1i/view?usp=sharing

How to use

• Requirements: Matlab 2017b or later version and at least one Nvidia GPU
• How to run the code?

1. Download and unzip the code
2. Unzip the folder "functions.zip" and "test_images"
3. Download the network file "coreNet.mat" from the link above
4. Copy the ""coreNet.mat" to the folder where you store the code or the matlab path
5. Add the "CoreNet-main" and its subfloders to your Matlab path
6. Run the "coreNet_predict.m"

• Note: The network highly demands GPU computation power (NVIDIA RTX A6000 is recommended)

Contact

Created by Jiawei Sun (jiawei.sun@tu-dresden.de) from TU Dresden - feel free to contact me!