A deep learning-based GPR forward solver for predicting B-scans of subsurface objects
The forward full-wave modeling of ground-penetrating radar (GPR) facilitates the understanding and interpretation of GPR data. Traditional forward solvers require excessive computational resources, especially when their repetitive executions are needed in signal processing and/or machine learning al...
Main Authors: | Dai, Qiqi, Lee, Yee Hui, Sun, Hai-Han, Qian, Jiwei, Ow, Genevieve, Mohamed Lokman Mohd Yusof, Yucel, Abdulkadir C. |
---|---|
Other Authors: | School of Electrical and Electronic Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/163834 |
Similar Items
-
Compact dual-polarized vivaldi antenna with high gain and high polarization purity for GPR applications
by: Sun, Hai-Han, et al.
Published: (2021) -
Estimating parameters of the tree root in heterogeneous soil environments via mask-guided multi-polarimetric integration neural network
by: Sun, Hai-Han, et al.
Published: (2022) -
The effect of grid size of the scanning line to GPR imaging /
by: Norsyazwani Musa, 1991-, et al.
Published: (2014) -
The effect of grid size of the scanning line to GPR imaging [electronic resource] /
by: Norsyazwani Musa, 1991-, et al.
Published: (2014) -
Tree roots reconstruction framework for accurate positioning in heterogeneous soil
by: Luo, Wenhao, et al.
Published: (2022)