Triplanar Imaging of 3-D GPR Data for Deep-Learning-Based Underground Object Detection-Reference-Cited by-同舟云学术

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Triplanar Imaging of 3-D GPR Data for Deep-Learning-Based Underground Object Detection

Published:2019-11 Issue:11 Volume:12 Page:4446-4456
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Kim Namgyu,Kim Sehoon,An Yun-Kyu^ORCID,Lee Jong-Jae^ORCID

Funder

Transportation Technology Promotion Research Program

Ministry of Land, Infrastructure and Transport

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Atmospheric Science,Computers in Earth Sciences

Link

http://xplorestaging.ieee.org/ielx7/4609443/8950468/08935527.pdf?arnumber=8935527

Cited by 34 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Analysis and Design of an Airborne-Dangled Monopole-Antenna Symmetric Remote-Sensing Radiation Source for Airport Runway Monitoring;Symmetry;2024-08-19

2. Deep learning based method for 3D reconstruction of underground pipes in 3D GPR C-scan data;Tunnelling and Underground Space Technology;2024-08

3. Automatic classification of underground utilities in Urban Areas: A novel method combining ground penetrating radar and image processing;Archives of Civil Engineering;2024-06-18

4. Automatic Object Detection in Radargrams of Multi-Antenna GPR Systems Based on Simulation Data for Railway Infrastructure Analysis;Applied Sciences;2024-04-22

5. 3D imaging and temporal evolution recognition of concrete internal defects based on GPR;Measurement Science and Technology;2024-03-28

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