Deep Learning-Enabled De-Noising of Fiber Bragg Grating-Based Glucose Sensor: Improving Sensing Accuracy of Experimental Data

Deep Learning-Enabled De-Noising of Fiber Bragg Grating-Based Glucose Sensor: Improving Sensing Accuracy of Experimental Data

This paper outlines the successful utilization of deep learning (DL) techniques to elevate data quality for assessing Au-TFBG (tilted fiber Bragg grating) sensor performance. Our approach involves a well-structured DL-assisted framework integrating a hierarchical composite attention mechanism. In or...

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Bibliographic Details
Main Authors: Harshit Tiwari, Yogendra S. Dwivedi, Rishav Singh, Anuj K. Sharma, Ajay Kumar Sharma, Richa Krishna, Nitin Singh Singha, Yogendra Kumar Prajapati, Carlos Marques
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Photonics
Subjects:
tilted fiber Bragg grating (TFBG)
glucose sensor
deep learning (DL)
figure of merit
attention network
sequential modelling
Online Access:https://www.mdpi.com/2304-6732/11/11/1058
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