Ground Penetrating Radar (GPR) is one of the NDT (Non-Destructive Techniques) in the geophysics field. Most Geoscientists accept the instrument's capability to conduct near-surface mapping. On the other side, the technology in deep learning vastly developed in many sectors, affecting the perspective of radar-images post-processing. The problem occurred when a lot of identical objects were detected in the GPR section. Hence, the interpreter will face difficulties when performing manual object detection on a large scale of the dataset. In this study, the deep learning algorithm attempted to be employed to forage the civil structures and deal with overtired work interpretations. This study specifies five structures from the dataset: Pile, Pipe, Powerline, Rebar, and Void/Collapse Structure. All objects are confirmed buried in the subsurface when field measurement is conducted. This study introduces a new approach to improving accuracy called IC-CNN (Integrated Contouring in Convolutional Neural Network). The IC-CNN method is expected to become an advanced technique to achieve solid identifications for GPR data through an object contour and object localization. The B-Scan of GPR Images was employed for the analysis. However, the primary processing of GPR data has been conducted to make it adequate as relevant input. As a result, it presented a correlation with a 95% confidence level. Furthermore, IC-CNN gave significance $\pm 3.5$ % rather than CNN for the GPR B-scan data, which was concluded after 2,500 iterations. In final, the IC-CNN is promising as long as it is well-processed.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Deep learning for Ground Penetration Radar Reflection Images in Civil Structures Investigation




    Publication date :

    2022-11-24


    Size :

    787073 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Deep penetration using surface contact HF radar

    Lynch, E.D. / Brown, R.D. / Mokry, D.D. et al. | Tema Archive | 1998


    Validation of Ground Penetration Radar Accuracy for Estimating Pavement Layer Thicknesses

    National Research Council (U.S.) | British Library Conference Proceedings | 2005


    Gültigkeit der mit dem "Ground Penetration Radar" (GPR) ermittelten Schichtdicken von Straßenbefestigungen

    Förster, Marc-Oliver / Hothan, Jürgen / Deutschland, Bundesministerium für Verkehr, Bau- und Wohnungswesen | TIBKAT | 2001


    Civil airborne radar

    Heller, D.M. | Engineering Index Backfile | 1954


    Civil aircraft radar

    Freedman, S. | Engineering Index Backfile | 1949