scholarly journals Neural Networks as a Tool for Georadar Data Processing

2015 ◽  
Vol 25 (4) ◽  
pp. 955-960 ◽  
Author(s):  
Piotr Szymczyk ◽  
Sylwia Tomecka-Suchoń ◽  
Magdalena Szymczyk
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Data Processing ◽  
Ground Penetrating Radar ◽  
Feature Vector ◽  
Special Kind ◽  
Automatic Classification ◽  
Geologic Structure ◽  
Ground Penetrating

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.

scholarly journals Automatic Classification of Ground-Penetrating-Radar Signals for Railway-Ballast Assessment

2011 ◽  
Vol 49 (10) ◽  
pp. 3961-3972 ◽  
Author(s):  
Wenbin Shao ◽  
Abdesselam Bouzerdoum ◽  
Son Lam Phung ◽  
Lijun Su ◽  
Buddhima Indraratna ◽  
...  
Keyword(s):  
Ground Penetrating Radar ◽  
Automatic Classification ◽  
Railway Ballast ◽  
Radar Signals ◽  
Ground Penetrating

scholarly journals Exploration of Pipelines from the use of GPR Data by Neural Network

2019 ◽  
Vol 8 (2S11) ◽  
pp. 3711-3715
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Ground Penetrating Radar ◽  
Buried Pipes ◽  
Adaptive Neural Networks ◽  
The World ◽  
Systematic Training ◽  
Ground Penetrating

Noticing about the buried pipes is a important issue, In many regions of the world. In spite of the fact that several techniques are there. This literature is used to find out the underground pipes automatically that provides accuracy execution is underway. Which gave amazing results Achieved by the deep learning of the different discoveries found in this article offer a pipeline to detect anti-personnel pipes Adaptive Neural Networks ( applied to the Ground Penetrating Radar (GPR). The proposed algorithm is suitable to recognize if the scanning format has been received. The acquisition of GPR has a track of anti-personnel pipes. The validity of the said system is made on a real GPR receipt, although systematic training can be done to have relied upon data generated by achievements. Based on the results 95% of the accuracy of detection got achieved without testing acquisition of pipes.

Ground-Penetrating Radar: Operation Principle and Data Processing

2019 ◽  
pp. 1-23 ◽  
Author(s):  
Ilaria Catapano ◽  
Gianluca Gennarelli ◽  
Giovanni Ludeno ◽  
Francesco Soldovieri ◽  
Raffaele Persico
Keyword(s):  
Data Processing ◽  
Ground Penetrating Radar ◽  
Ground Penetrating
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