Underground Cylindrical Objects Detection and Diameter Identification in GPR B-Scans via the CNN-LSTM Framework

Underground Cylindrical Objects Detection and Diameter Identification in GPR B-Scans via the CNN-LSTM Framework

Ground penetrating radar (GPR), as a non-invasive instrument, has been widely used in the civil field. The interpretation of GPR data plays a vital role in underground infrastructures to transfer raw data to the interested information, such as diameter. However, the diameter identification of object...

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Bibliographic Details
Main Authors: Wentai Lei, Jiabin Luo, Feifei Hou, Long Xu, Ruiqing Wang, Xinyue Jiang
Format: Article
Language:English
Published: MDPI AG 2020-10-01
Series:Electronics
Subjects:
ground penetrating radar (GPR)
hyperbola region detection
Convolutional Neural Network (CNN)
Long Short-Term Memory (LSTM)
hyperbola classification
diameter identification
Online Access:https://www.mdpi.com/2079-9292/9/11/1804

Internet

https://www.mdpi.com/2079-9292/9/11/1804

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