Convolutional Neural Networks for Water Content Classification and Prediction With Ground Penetrating Radar

Convolutional Neural Networks for Water Content Classification and Prediction With Ground Penetrating Radar

A novel ground penetrating radar (GPR)-based subsurface water content classification and prediction technique using deep neural networks is proposed. The fantastic advantages of deep network in classification and regression tasks show the huge potential to measure soil moisture content status quickl...

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Bibliographic Details
Main Authors: Jing Zheng, Xingzhi Teng, Jie Liu, Xu Qiao
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Water content
CNN
GPR
classification
regression
Online Access:https://ieeexplore.ieee.org/document/8936955/

Internet

https://ieeexplore.ieee.org/document/8936955/

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