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Enhanced Image Reconstruction in Electrical Impedance Tomography using Radial Basis Function Neural Networks Cover

Enhanced Image Reconstruction in Electrical Impedance Tomography using Radial Basis Function Neural Networks

Measurement Science Review
Volume 24 (2024): Issue 6 (December 2024)
By: Serge Ayme Kouakouo Nomvussi and  Jan Mikulka  
Open Access
|Dec 2024

Authors

Serge Ayme Kouakouo Nomvussi

244245@vut.cz

Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, Antonínská 548/1, Brno, Czech Republic

Jan Mikulka

mikulka@vut.cz

Department of Theoretical and Experimental Electrical Engineering, Brno University of Technology, Antonínská 548/1, Brno, Czech Republic
DOI: https://doi.org/10.2478/msr-2024-0027 | Journal eISSN: 1335-8871
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Language: English
Page range: 200 - 210
Submitted on: Jul 26, 2024
Accepted on: Nov 6, 2024
Published on: Dec 24, 2024
Published by: Slovak Academy of Sciences, Institute of Measurement Science
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open
Keywords:
Artificial neural network,
density-based algorithm,
electrical impedance tomography,
k-nearest neighbors,
radial basis function neural networks,
EIDORS framework
Related subjects:
Engineering,
Electrical engineering,
Control engineering, metrology and testing

© 2024 Serge Ayme Kouakouo Nomvussi, Jan Mikulka, published by Slovak Academy of Sciences, Institute of Measurement Science
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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