USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS  IN ELECTRICAL IMPEDANCE TOMOGRAPHY

Grzegorz  Kłosowski; Tomasz  Rymarczyk

doi:10.5604/01.3001.0010.5226

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Published: Sep 30, 2017

DOI: https://doi.org/10.5604/01.3001.0010.5226

DOI

https://doi.org/10.5604/01.3001.0010.5226

Authors

Grzegorz Kłosowski

g.klosowski@pollub.pl

Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise

Tomasz Rymarczyk

tomasz@rymarczyk.com

Research and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin

Abstract

This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Networks in impedance tomography. Machine Learning methods can be used to teach computers different technical problems. The efficient use of conventional artificial neural networks in tomography is possible able to effectively visualize objects. The first step of implementation Deep Learning methods in Electrical Impedance Tomography was performed in this work.

Keywords:

Imaging tomography, Multilayer Perceptron, Deep Learning, Convolutional Neural Networks

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Kłosowski, G. ., & Rymarczyk, T. . (2017). USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 7(3), 99–102. https://doi.org/10.5604/01.3001.0010.5226

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