Applications of Ground-Penetrating Radar (GPR) to Detect Hidden Beam Positions
Source abstract
Abstract
Abstract Ground-penetrating radar (GPR) uses electromagnetic waves to investigate the structures. In this investigation method, an electromagnetic wave is transmitted using an antenna and the received signal is recorded. Detection of beam positions in this GPR data requires the skills of a trained human operator. This study utilized a multi-layer neural network to detect beam positions in the GPR data. The visual description and definition of GPR data has major disadvantages and a neural network has been studied to overcome these shortcomings. A set of 32,740 training vectors with a length of 64 data was implemented to train the neural network. A new set of 16,370 testing vectors with a length of 64 data was then prepared to test the performance. Testing results suggest that the neural network is promising methods for the detection of beam positions in the GPR data.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Geophysical Methods and Applications · Seismic Waves and Analysis · Underwater Acoustics Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Dept. of Civil Engineering, Izmir Univ. of Economics 1 , Izmir, TR
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