A detection and classification algorithm of underground cable targets using ground penetrating radar based on YOLOv5

Yuancheng Wei

doi:10.1117/12.3031028

19 July 2024 A detection and classification algorithm of underground cable targets using ground penetrating radar based on YOLOv5

Yuancheng Wei

Author Affiliations +

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131813X (2024) https://doi.org/10.1117/12.3031028
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

Ground Penetrating Radar (GPR) offers the benefits of non-destructive testing (NDT) and high efficiency, making it extensively employed for subsurface material detection. However, conventional GPR image interpretation heavily relies on researchers' experiential knowledge, which will lead to reduced detection efficiency and more recognition errors. To address these challenges, this study proposes a new technology to achieve GPR detection in high efficiency. By enhancing the network structure of YOLOv5 through incorporating attention mechanisms, data augmentation techniques, and other approaches, we aim to mitigate issues related to false detections and missed identifications during real-time GPR-based localization of directly buried underground cables.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuancheng Wei "A detection and classification algorithm of underground cable targets using ground penetrating radar based on YOLOv5", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131813X (19 July 2024); https://doi.org/10.1117/12.3031028

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