USING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY


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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Published : 2017-09-30


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

Grzegorz Kłosowski  g.klosowski@pollub.pl
Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise  Poland
Tomasz Rymarczyk 
Research and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin  Poland