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Research on the Tunnel Geological Radar Image Flaw Detection Based on CNN Cover

Research on the Tunnel Geological Radar Image Flaw Detection Based on CNN

By: He Li and  Yubian Wang  
Open Access
|Feb 2022

Figures & Tables

Figure 1.

GPR system detection equipment
GPR system detection equipment

Figure 2.

Principles of geological radar detection
Principles of geological radar detection

Figure 3.

GPR image of tunnel ejection
GPR image of tunnel ejection

Figure 4.

Structure chart Faster RCNN
Structure chart Faster RCNN

Figure 5.

Structure chart of RPN
Structure chart of RPN

Figure 6.

Same border regression of IoU
Same border regression of IoU

Figure 7.

Network model training process
Network model training process

DIELECTRIC CONSTANTS OF COMMON MATERIALS

MaterialDielectric constantVelocity (mm/ns)
atmosphere1300
water8130
concrete5-855-120
Sand (dry)3-6120-170
Sand (wet)25-3055-60
pitch3-5134-173
Language: English
Page range: 44 - 53
Published on: Feb 23, 2022
Published by: Xi’an Technological University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2022 He Li, Yubian Wang, published by Xi’an Technological University
This work is licensed under the Creative Commons Attribution 4.0 License.