[HTML][HTML] Logistic regression for machine learning in process tomography
The main goal of the research presented in this paper was to develop a refined machine
learning algorithm for industrial tomography applications. The article presents algorithms …
learning algorithm for industrial tomography applications. The article presents algorithms …
[HTML][HTML] The use of time-frequency moments as inputs of lstm network for ecg signal classification
This paper refers to the method of using the deep neural long-short-term memory (LSTM)
network for the problem of electrocardiogram (ECG) signal classification. ECG signals …
network for the problem of electrocardiogram (ECG) signal classification. ECG signals …
[PDF][PDF] Maintenance of industrial reactors supported by deep learning driven ultrasound tomography
Monitoring of industrial processes is an important element ensuring the proper maintenance
of equipment and high level of processes reliability. The presented research concerns the …
of equipment and high level of processes reliability. The presented research concerns the …
[HTML][HTML] Comparison of selected machine learning algorithms for industrial electrical tomography
The main goal of this work was to compare the selected machine learning methods with the
classic deterministic method in the industrial field of electrical impedance tomography. The …
classic deterministic method in the industrial field of electrical impedance tomography. The …
[HTML][HTML] Optimising the use of Machine learning algorithms in electrical tomography of building Walls: Pixel oriented ensemble approach
This paper presents the results of research on identifying moisture inside the walls of
buildings with the use of electrical impedance tomography (EIT). The original, complex pixel …
buildings with the use of electrical impedance tomography (EIT). The original, complex pixel …
[HTML][HTML] Comparison of machine learning methods in electrical tomography for detecting moisture in building walls
This paper presents the results of research on the use of machine learning algorithms and
electrical tomography in detecting humidity inside the walls of old buildings and structures …
electrical tomography in detecting humidity inside the walls of old buildings and structures …
[HTML][HTML] Quality assessment of the neural algorithms on the example of EIT-UST hybrid tomography
The paper presents the results of research on the hybrid industrial tomograph electrical
impedance tomography (EIT) and ultrasonic tomography (UST)(EIT-UST), operating on the …
impedance tomography (EIT) and ultrasonic tomography (UST)(EIT-UST), operating on the …
[HTML][HTML] Historical buildings dampness analysis using electrical tomography and machine learning algorithms
The article deals with the problem of detecting moisture in the walls of historical buildings.
As part of the presented research, the following four methods based on mathematical …
As part of the presented research, the following four methods based on mathematical …
[HTML][HTML] Plug regime flow velocity measurement problem based on correlability notion and twin plane electrical capacitance tomography: Use case
V Mosorov, G Rybak, D Sankowski - Sensors, 2021 - mdpi.com
In this paper, the authors present the flow velocity measurement based on twin plane sensor
electrical capacitance tomography and the cross-correlation method. It is shown that such a …
electrical capacitance tomography and the cross-correlation method. It is shown that such a …
[HTML][HTML] Improvement of flow velocity measurement algorithms based on correlation function and twin plane electrical capacitance tomography
This article discusses the correlation method for time delay estimation, its disadvantages,
and drawbacks. It is shown that the correlation method for material velocity measurement …
and drawbacks. It is shown that the correlation method for material velocity measurement …