91 citations
10 papers
A Migration-Assisted Deep Learning Scheme for Imaging Defects Inside Cylindrical Structures via GPR: A Case Study for Tree Trunks
Jiwei Qian, Yee Hui Lee, Kaixuan Cheng +5
Ground-penetrating radar (GPR) has emerged as a prominent tool for imaging internal defects in cylindrical structures, such as columns, utility poles, and tree trunks. However, acc…
A Deep Learning-Augmented Stand-off Radar Scheme for Rapidly Detecting Tree Defects
Jiwei Qian, Yee Hui Lee, Kaixuan Cheng +4
Tree defect detection is crucial for the structural health screening of trees. Existing nondestructive testing (NDT) techniques for tree defect detection require time-consuming and…
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data Inversion
Qiqi Dai, Yee Hui Lee, Hai-Han Sun +3
The reconstruction of the 3D permittivity map from ground-penetrating radar (GPR) data is of great importance for mapping subsurface environments and inspecting underground structu…
A Deep Learning-Based GPR Forward Solver for Predicting B-Scans of Subsurface Objects
Qiqi Dai, Yee Hui Lee, Hai-Han Sun +4
The forward full-wave modeling of ground-penetrating radar (GPR) facilitates the understanding and interpretation of GPR data. Traditional forward solvers require excessive computa…
Accurate Tree Roots Positioning and Sizing over Undulated Ground Surfaces by Common Offset GPR Measurements
Wenhao Luo, Yee Hui Lee, Lai Fern Ow +2
Tree roots detection is a popular application of the Ground-penetrating radar (GPR). Normally, the ground surface above the tree roots is assumed to be flat, and standard processin…
DMRF-UNet: A Two-Stage Deep Learning Scheme for GPR Data Inversion under Heterogeneous Soil Conditions
Qiqi Dai, Yee Hui Lee, Hai-Han Sun +3
Traditional ground-penetrating radar (GPR) data inversion leverages iterative algorithms which suffer from high computation costs and low accuracy when applied to complex subsurfac…