Enhancing Accuracy in Gas–Water Two-Phase Flow Sensor Systems Through Deep-Learning- Based Computational Framework

Bao, M., Wu, R., Wang, M. et al. (2 more authors) (2024) Enhancing Accuracy in Gas–Water Two-Phase Flow Sensor Systems Through Deep-Learning- Based Computational Framework. IEEE Sensors Journal, 24 (23). pp. 39934-39946. ISSN 1530-437X

Abstract

Metadata

Item Type: Article
Authors/Creators:
Keywords: Deep learning; fluid flow measurement; neural networks; sensor systems; tomography
Dates:
  • Published: 1 December 2024
  • Published (online): 11 October 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds)
The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 07 Jan 2025 15:51
Last Modified: 07 Jan 2025 15:51
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: 10.1109/jsen.2024.3475292
Open Archives Initiative ID (OAI ID):

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