3DInvNet: a deep learning-based 3D ground-penetrating radar data inversion

3DInvNet: a deep learning-based 3D ground-penetrating radar data inversion

The reconstruction of the 3D permittivity map from ground-penetrating radar (GPR) data is of great importance for mapping subsurface environments and inspecting underground structural integrity. Traditional iterative 3D reconstruction algorithms suffer from strong non-linearity, ill-posedness, an...

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Bibliographic Details
Main Authors: Dai, Qiqi, Lee, Yee Hui, Sun, Hai-Han, Ow, Genevieve, Yusof, Mohamed Lokman Mohd, Yucel, Abdulkadir C.
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Electrical and electronic engineering
Deep Learning
Denoising
Online Access:https://hdl.handle.net/10356/169999

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