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Erschienen in:
Application of Image Classification for Fine-Grained Nudity Detection Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

Rebar Detection and Localization for Non-destructive Infrastructure Evaluation of Bridges Using Deep Residual Networks

verfasst von : Habib Ahmed, Hung Manh La, Gokhan Pekcan

Erschienen in: Advances in Visual Computing

Verlag: Springer International Publishing

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Abstract

Nondestructive Evaluation (NDE) of civil infrastructure has been an active area of research for the past few decades. Traditional inspection of civil infrastructure, mostly relying on visual inspection is time-consuming, labor-intensive and often provides subjective and erroneous results. To facilitate this process, different sensors for data collection and techniques for data analyses have been used to effectively carry out this task in an automated manner. The purpose of this research is to provide a novel Deep Learning-based method for detection of steel rebars in reinforced concrete bridge elements using data from Ground Penetrating Radar (GPR). At the same time, a novel technique is proposed for the localization of rebar in B-scan images. In order to examine the performance of the rebar detection and localization system, results are outlined to demonstrate the feasibility of the proposed system within relevant practical applications.

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Vorheriges Kapitel An Automatic Digital Terrain Generation Technique for Terrestrial Sensing and Virtual Reality Applications
Nächstes Kapitel Intrinsic Decomposition by Learning from Varying Lighting Conditions
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Metadaten
Titel
Rebar Detection and Localization for Non-destructive Infrastructure Evaluation of Bridges Using Deep Residual Networks
verfasst von
Habib Ahmed
Hung Manh La
Gokhan Pekcan
Copyright-Jahr
2019
Buch
Advances in Visual Computing

Print ISBN: 978-3-030-33719-3

Electronic ISBN: 978-3-030-33720-9

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-33720-9_49

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