ECT-LSTM-RNN: An Electrical Capacitance Tomography Model-Based Long Short-Term Memory Recurrent Neural Networks for Conductive Materials

ECT-LSTM-RNN: An Electrical Capacitance Tomography Model-Based Long Short-Term Memory Recurrent Neural Networks for Conductive Materials

Image reconstruction for industrial applications based on Electrical Capacitance Tomography (ECT) has been broadly applied. The goal of image reconstruction based ECT is to locate the distribution of permittivity for the dielectric substances along the cross-section based on the collected capacitanc...

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Bibliographic Details
Main Authors: Wael Deabes, Alaa Sheta, Malik Braik
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Image reconstruction
long short-term memory recurrent neural network
lost foam casting
metal filling process
Online Access:https://ieeexplore.ieee.org/document/9429218/

Internet

https://ieeexplore.ieee.org/document/9429218/

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