蒋鹏
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Arbitrarily-oriented tunnel lining defects detection from Ground Penetrating Radar images using deep Convolutional Neural networks
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Affiliation of Author(s): : 控制科学与工程学院

Title of Paper: : Arbitrarily-oriented tunnel lining defects detection from Ground Penetrating Radar images using deep Convolutional Neural networks

Journal: : Automation in Construction

Key Words: : Arbitrarily-oriented defect detection;Automation;Deep learning;Ground penetrating radar;Tunnel inspection

First Author: : 王静

Document Code: : 1523583211215523842

Volume: : 133

Number of Words: : 50

Translation or Not: : no

Date of Publication: : 2021-11-13

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Associate Professor

Gender : Male

Status : Employed

School/Department : 齐鲁交通学院

Date of Employment : 2018-09-17

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