Improved Spectral Interrogation of Tilted Fiber Bragg Grating Refractometer Using Residual Convolutional Neural Networks-Reference-Cited by-同舟云学术

Improved Spectral Interrogation of Tilted Fiber Bragg Grating Refractometer Using Residual Convolutional Neural Networks

Published:2022-11-15 Issue:22 Volume:40 Page:7403-7411
ISSN:0733-8724
Container-title:Journal of Lightwave Technology
language:
Short-container-title:J. Lightwave Technol.

Author:

Cao Zihan¹,Xia Titi¹,Zhang Shengqi¹,Zhang Shuhe¹,Mei Yongchang¹^ORCID,Liu Zhengyong¹^ORCID,Guo Tuan²^ORCID,Li Zhaohui¹^ORCID

Affiliation:

1. Guangdong Provincial Key Laboratory of Optoelectronic Information Processing Chips and Systems, School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China

2. Institute of Photonics Technology, Jinan University, Guangzhou, China

Funder

National Natural Science Foundation of China

Department of Natural Resources of Guangdong Province

Marine Economy Development Special Fund Six Marine Industries

Science and Technology Planning Project of Guangzhou

Southern Marine Science and Engineering Guangdong Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atomic and Molecular Physics, and Optics

Link

http://xplorestaging.ieee.org/ielx7/50/9945622/09865163.pdf?arnumber=9865163

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4. Refractometric Sensitivity Enhancement of Weakly Tilted Fiber Bragg Grating Integrated with Black Phosphorus

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