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.W artykule zaprezentowano dwa przypadki dotyczące zastosowania sztucznych sieci neuronowych i konwolucyjnych sieci neuronowychw tomografii impedancyjnej. Uczenie maszynowe może znaleźć zastosowanie przy rozwiązywaniu różnorodnych problemów technicznych.W tomograficznej rekonstrukcji obrazó...
Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications....
Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction method for a...
Abstract Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction me...
This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Net...
The article presents the results of research in the area of using deep neural networks to identify m...
We consider the problem of the detection of brain hemorrhages from three-dimensional (3D) electrical...
Electrical impedance tomography (EIT) has been widely used in biomedical research because of its adv...
The article presents the results of research in the area of using deep neural networks to identify m...
The article presents four selected methods of supervised machine learning, which can be successfully...
Electrical impedance tomography (EIT) does imaging by solving a nonlinear ill-posed inverse problem....
Electrical impedance tomography is a differential tomography method where current is injected into a...
This thesis is concerned with Electrical Impedance Tomography (EIT), an imaging technique in which p...
The mathematical problem for electrical impedance tomography (EIT) is a highly nonlinear ill-posed i...
Some problems in the field of health or industry require to obtain information from the inside of a ...
This paper was presented a practical method of solving inverse problems in tomography using neural n...
Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications....
Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction method for a...
Abstract Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction me...
This paper refers to the cases of the use of Artificial Neural Networks and Convolutional Neural Net...
The article presents the results of research in the area of using deep neural networks to identify m...
We consider the problem of the detection of brain hemorrhages from three-dimensional (3D) electrical...
Electrical impedance tomography (EIT) has been widely used in biomedical research because of its adv...
The article presents the results of research in the area of using deep neural networks to identify m...
The article presents four selected methods of supervised machine learning, which can be successfully...
Electrical impedance tomography (EIT) does imaging by solving a nonlinear ill-posed inverse problem....
Electrical impedance tomography is a differential tomography method where current is injected into a...
This thesis is concerned with Electrical Impedance Tomography (EIT), an imaging technique in which p...
The mathematical problem for electrical impedance tomography (EIT) is a highly nonlinear ill-posed i...
Some problems in the field of health or industry require to obtain information from the inside of a ...
This paper was presented a practical method of solving inverse problems in tomography using neural n...
Electrical Impedance Tomography (EIT) is a powerful non-invasive technique for imaging applications....
Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction method for a...
Abstract Objective: To develop, and demonstrate the feasibility of, a novel image reconstruction me...