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Neural Networks as a Tool for Georadar Data Processing Cover

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.

DOI: https://doi.org/10.1515/amcs-2015-0068 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 955 - 960
Submitted on: Jul 7, 2014
Published on: Dec 30, 2015
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2015 Piotr Szymczyk, Sylwia Tomecka-Suchoń, Magdalena Szymczyk, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.