Urban Subsurface Mapping via Deep Learning Based GPR Data Inversion
Author:
Affiliation:
1. The University of Tennessee,Department of Civil and Environmental Engineering,Knoxville,TN,USA,37996
2. School of Civil & Environmental Engineering and Construction Management, The University of Texas at San Antonio,San Antonio,TX,USA,78207
Funder
NSF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10015196/10015230/10015357.pdf?arnumber=10015357
Reference43 articles.
1. Counting Instances of Objects in Color Images Using U-Net Network on Example of Honey Bees;westwa?ska;2019 Federated Conference on Computer Science and Information Systems (FedCSIS),2019
2. Machine Learning in Object Recognition and Segmentation by Certain Class Neural Networks
3. Uncertainty-aware visualization and proximity monitoring in urban excavation: a geospatial augmented reality approach
4. Buried object detection and analysis of GPR images: Using neural network and curve fitting
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2. Underground infrastructure detection and localization using deep learning enabled radargram inversion and vision based mapping;Automation in Construction;2023-10
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