Drone Aided Machine-Learning Tool for Post-Earthquake Bridge Damage Reconnaissance

About this item

Title

Drone Aided Machine-Learning Tool for Post-Earthquake Bridge Damage Reconnaissance

Content partner

University of Canterbury Library

Collection

UC Research Repository

Description

After a high-intensity seismic event, inspections of structural damages need to be carried out as soon as possible in order to optimize the emergency management, as well as improving the recovery time. In the current practice, damage inspections are performed by an experienced engineer, who physically inspect the structures. This way of doing not only requires a significant amount of time and high skilled human resources, but also raises the concern about the inspector’s safety. A promising a...

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Format

Research paper

Research format

Conference item

Date created

2020

Creator

Ma Z / Zhao E / Granello G / Loporcaro G

URL

https://hdl.handle.net/10092/101461

Related subjects

post-earthquake reconnaissance / drone inspection / machine-learning / Engineering / Civil engineering / Earthquake engineering / Communications engineering / Wireless communication systems and technologies (incl. microwave and millimetrewave)

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You can learn more about the rights status of this item at: http://hdl.handle.net/10092/17651

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