<abstract xmlns="http://www.w3.org/1999/xhtml"><p>In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.</p></abstract>

In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector) are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

Neural Networks as a Tool for Georadar Data Processing

Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland

Department of Geophysics, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland

International Journal of Applied Mathematics and Computer Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Neural Networks as a Tool for Georadar Data Processing"}

In this article a new neural network based method for automatic classification of ground penetrating radar (GPR) traces is proposed. The presented approach is...

Neural Networks as a Tool for Georadar Data Processing

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 955 - 960

Eingereicht: 07. Juli 2014

DOI: https://doi.org/10.1515/amcs-2015-0068

Schlüsselwörter
neural networks, artificial neural networks, ground penetrating radar, classification of a geological structure, sinkhole

© 2015 Piotr Szymczyk et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Neural Networks as a Tool for Georadar Data Processing

Online veröffentlicht: 30. Dez. 2015

Seitenbereich: 955 - 960

Eingereicht: 07. Juli 2014

DOI: https://doi.org/10.1515/amcs-2015-0068

Schlüsselwörterneural networks, artificial neural networks, ground penetrating radar, classification of a geological structure, sinkhole

© 2015 Piotr Szymczyk et al., published by De Gruyter Open

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
neural networks, artificial neural networks, ground penetrating radar, classification of a geological structure, sinkhole