Open AccessUSING NEURAL NETWORKS AND DEEP LEARNING ALGORITHMS IN ELECTRICAL IMPEDANCE TOMOGRAPHY
Author(s) -
Grzegorz Kłosowski,
Tomasz Rymarczyk
Publication year - 2017
Publication title -
informatyka, automatyka, pomiary w gospodarce i ochronie środowiska
Language(s) - English
Resource type - Journals
eISSN - 2391-6761
pISSN - 2083-0157
DOI - 10.5604/01.3001.0010.5226
Subject(s) - electrical impedance tomography , artificial neural network , convolutional neural network , deep learning , computer science , artificial intelligence , tomography , electrical impedance , algorithm , machine learning , engineering , electrical engineering , physics , optics
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.