山东大学教师主页蒋鹏 GPRI2Net: A Deep-Neural-Network-Based Ground Penetrating Radar Data Inversion and Object Identification Framework for Consecutive and Long Survey Lines Home

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GPRI2Net: A Deep-Neural-Network-Based Ground Penetrating Radar Data Inversion and Object Identification Framework for Consecutive and Long Survey Lines

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Institution:控制科学与工程学院

Title of Paper:GPRI2Net: A Deep-Neural-Network-Based Ground Penetrating Radar Data Inversion and Object Identification Framework for Consecutive and Long Survey Lines

Journal:IEEE Transactions on Geoscience and Remote Sensing

First Author:王静

Document Code:34478BFE861B467EBEE8E61FBE8A4FFF

Volume:60

Number of Words:10

Translation or Not:No

Date of Publication:2021-09

Release Time:2022-05-22

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Personal information

Professor

Gender : Male

Status : Employed

School/Department : 齐鲁交通学院

Date of Employment : 2018-09-17

Faculty/School : School of Qilu Transportation

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