• Corrosion Science and Technology
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• v.3 no.6
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• pp.262-264
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• 2004

Ground Penetrating Radar (GPR) has been used to image inside concrete specimens embedded with steel bars and delamination. An imaging algorithm has been developed to improve measurement output generated from a commercial radar system. For the experiments, laboratory size concrete specimens are made with the dimensions of $1,000mm(W){\times}1,000mm(L){\times}250mm(D)$. The results have shown improved output of the radar measurements compared to commercially available processing methods.

• Economic and Environmental Geology
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• v.29 no.6
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• pp.745-752
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• 1996

A ground penetrating radar survey with a 500 MHz radar antenna was applied to make archaeological investigation in Nakajima of Ishikawa Prefecture, Japan. The ability of the radar system to aid in the archaeological preservation of burial ground was the primary concern of the experiments. The average variance of the radar wave returned from progressively deeper reflectors in a tomb were contoured at 2.4 nanoseconds intervals. The results of analysis indicates the location of trenches and the coffin area at the tomb site. The orientation of the coffin is dearly defined on contour maps made below 9.6 nanoseconds horizon. The general features detected by the GPR were also reconfirmed by electric resistivity survey made at the site. The radar was accurate in ascertaining the location, orientation, and the general construction style of the coffin.

• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.88-92
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• 2004

To improve the recovery rate of unlocated buried human remains in forensic investigations, there is scope to evaluate and develop techniques that are applicable to the Australian environment. I established controlled gravesites (comprising shallow buried kangaroos, pigs, and human cadavers) in South Australia, to allow the methodical testing of remote sensing equipment for the purpose of grave detection in forensic investigations. Eight-month-old pig graves are shown to provide more distinct identifying results using ground-penetrating radar when compared to four-year-old kangaroo graves. Two further aspects of this research are presented: information (obtained from a survey) relating to the police use of geophysical instruments for locating buried human remains, and the use of electrical resistivity for locating human remains buried in a coffin. The survey of Australian police jurisdictions, covering the period 1995-2000, showed that police searches for unlocated bodies have not successfully located human remains using any geophysical instruments (such as ground-penetrating radar, magnetometers, or electrical resistivity). Lower resistivity readings were found coincident with the 150-year-old single historical burial in a heavily excavated field, in a situation where its exact location was previously unknown.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.509-516
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• 2011

In this paper, a ground penetrating radar(GPR) system is implemented for landmine detection. The performance of the GPR system is associated with the characteristics of local soil and buried target. The choice of the center frequency and the bandwidth of the GPR system are the key factors in the GPR system design. To detect a small and shallow target, the higher frequencies are needed for high depth resolution. We have been designed, fabricated and tested a new impulse generator using step recovery diodes. The measured impulse response has an amplitude of 6.2V and a pulse width of 250ps. The implemented GPR system has been tested real environmental conditions and has proved its ability to detect a small buried target.

• Geomechanics and Engineering
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• v.38 no.1
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• pp.29-44
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• 2024

This research investigates the effectiveness of data augmentation techniques in the automated analysis of B-scan images from ground-penetrating radar (GPR) using deep learning. In spite of the growing interest in automating GPR data analysis and advancements in deep learning for image classification and object detection, many deep learning-based GPR data analysis studies have been limited by the availability of large, diverse GPR datasets. Data augmentation techniques are widely used in deep learning to improve model performance. In this study, we applied four data augmentation techniques (geometric transformation, color-space transformation, noise injection, and applying kernel filter) to the GPR datasets obtained from a testbed. A deep learning model for GPR data analysis was developed using three models (Faster R-CNN ResNet, SSD ResNet, and EfficientDet) based on transfer learning. It was found that data augmentation significantly enhances model performance across all cases, with the mAP and AR for the Faster R-CNN ResNet model increasing by approximately 4%, achieving a maximum mAP (Intersection over Union = 0.5:1.0) of 87.5% and maximum AR of 90.5%. These results highlight the importance of data augmentation in improving the robustness and accuracy of deep learning models for GPR B-scan analysis. The enhanced detection capabilities achieved through these techniques contribute to more reliable subsurface investigations in geotechnical engineering.

• Structural Monitoring and Maintenance
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• v.1 no.2
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• pp.197-211
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• 2014

An investigation of tunnel linings is performed at two tunnels in the US using complimentary noncontact techniques: air-coupled ground penetrating radar (GPR), and a vehicle-mounted scanning system (SPACETEC) that combines laser, visual, and infrared thermography scanning methods. This paper shows that a combination of such techniques can maximize inspection coverage in a comprehensive and efficient manner. Since ground-truth is typically not available in public tunnel field evaluations, the noncontact techniques used are compared with two reliable in-depth contact nondestructive testing methods: ground-coupled GPR and ultrasonic tomography. The noncontact techniques are used to identify and locate the reinforcement mesh, structural steel ribs, internal layer interfaces, shallow delamination, and tile debonding. It is shown that this combination of methods can be used synergistically to provide tunnel owners with a comprehensive and efficient approach for monitoring tunnel lining conditions.

• Journal of electromagnetic engineering and science
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• v.16 no.3
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• pp.182-190
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• 2016

The problem of resolution in antenna ground-penetrating radar (GPR) is very important for the investigation and detection of buried targets. We should solve this problem with software or a numeric method. The purposes of this paper are the modelling and simulation resolution of antenna radar GPR using three antennas, arrays (as in the software REFLEXW), the antenna dipole (as in GprMax2D), and a bow-tie antenna (as in the experimental results). The numeric code has been developed for study resolution antennas by scattered electric fields in mode B-scan. Three frequency antennas (500, 800, and 1,000 MHz) have been used in this work. The simulation results were compared with experimental results obtained by Rial and colleagues under the same conditions.

• KCI Concrete Journal
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• v.12 no.1
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• pp.139-144
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• 2000

Ground Penetrating Radar (GPR) with 1 GHz antenna has been used to locate a steel bar embedded inside laboratory-prepared mortar specimens. Four mortar specimens are made with the dimensions of 100 cm (length) x 100 cm (width) x 14 cm (depth). One specimen had no bars and the other three specimens had a Dl9 steel bar at 4, 6. and 8 cm depth. As a part of the experimental work, the dielectric constants of mortar specimens are measured during curing. As the curing time increased. the dielectric constant decreased with decreasing moisture content inside the specimen. The steel bar embedded inside mortar specimens has been successfully identified in all three cases. The results using signal processing scheme developed in this study significantly improved the output of a commercially available radar system.

• Journal of the Korea Construction Safety Engineering Association
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• s.32
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• pp.62-66
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• 2005

• Proceedings of the Korean Geotechical Society Conference
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• 1993.06f
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• pp.1-14
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• 1993