@inproceedings{78a265971a414d3f84105de58080b60a,
title = "Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network",
abstract = "This work demonstrates a computational method for predicting the light propagation through a single multimode fiber using a deep neural network. The experiment for gathering training and testing data is performed with a digital micro-mirror device that enables the spatial light modulation. The modulated patterns on the device and the captured intensity-only images by the camera form the aligned data pairs. This sufficiently-trained deep neural network frame has very excellent performance for directly inferring the intensity-only output delivered though a multimode fiber. The model is validated by three standards: the mean squared error (MSE), the correlation coefficient (corr) and the structural similarity index (SSIM).",
keywords = "computational imaging, deep neural network, light propagation, multimode fibers",
author = "Pengfei Fan and Liang Deng and Lei Su",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd IEEE Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018 ; Conference date: 12-10-2018 Through 14-10-2018",
year = "2018",
month = dec,
day = "14",
doi = "10.1109/IAEAC.2018.8577930",
language = "English",
series = "Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1080--1084",
editor = "Bing Xu",
booktitle = "Proceedings of 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference, IAEAC 2018",
}