Application of Deep Neural Network to the Reconstruction of Two-Phase Material Imaging by Capacitively Coupled Electrical Resistance Tomography

Application of Deep Neural Network to the Reconstruction of Two-Phase Material Imaging by Capacitively Coupled Electrical Resistance Tomography

A convolutional neural network (CNN)-based image reconstruction algorithm for two-phase material imaging is presented and verified with experimental data from a capacitively coupled electrical resistance tomography (CCERT) sensor. As a contactless version of electrical resistance tomography (ERT), C...

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Bibliographic Details
Main Authors: Zhuoran Chen, Gege Ma, Yandan Jiang, Baoliang Wang, Manuchehr Soleimani
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Electronics
Subjects:
convolutional neural network (CNN)
supervised deep learning
capacitively coupled electrical resistance tomography (CCERT)
image reconstruction
Online Access:https://www.mdpi.com/2079-9292/10/9/1058

Internet

https://www.mdpi.com/2079-9292/10/9/1058

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