Surface Defect Detection, Segmentation and Quantification for Concrete Bridge Assessment Using Deep Learning and 3D Reconstruction

Surface Defect Detection, Segmentation and Quantification for Concrete Bridge Assessment Using Deep Learning and 3D Reconstruction
Title Surface Defect Detection, Segmentation and Quantification for Concrete Bridge Assessment Using Deep Learning and 3D Reconstruction PDF eBook
Author Chaobo Zhang
Publisher
Pages 119
Release 2020
Genre
ISBN

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Smart Multimedia

Smart Multimedia
Title Smart Multimedia PDF eBook
Author Stefano Berretti
Publisher Springer Nature
Pages 466
Release 2022-12-13
Genre Computers
ISBN 3031220617

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This book constitutes the proceedings of the Third International Conference on Smart Multimedia, ICSM 2022, which was held in Marseille, France, during August 25–27, 2022. The 30 full papers and 4 short paper presented in this volume were carefully reviewed and selected from 68 submissions. The contributions were organized in topical sections as follows: Machine Learning for Multimedia; Image Processing; Multimedia Applications; Multimedia for Medicine and Health-Care; Smart Homes; Multimedia Environments and Metaverse; Deep Learning on Video and Music; Haptic; Industrial.

Automated Bridge Inspection for Concrete Surface Defect Detection Using Deep Neural Network Based on LiDAR Scanning

Automated Bridge Inspection for Concrete Surface Defect Detection Using Deep Neural Network Based on LiDAR Scanning
Title Automated Bridge Inspection for Concrete Surface Defect Detection Using Deep Neural Network Based on LiDAR Scanning PDF eBook
Author Majid Nasrollahi
Publisher
Pages 0
Release 2020
Genre
ISBN

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Structural inspection and maintenance of bridges are essential to improve the safety and sustainability of the infrastructure systems. Visual inspection using non-equipped eyes is the principal method of detecting surface defects of bridges, which is time-consuming, unsafe, and encounters inspectors falling risks. Therefore, there is a need for automated bridge inspection. Recently, Light Detection and Ranging (LiDAR) scanners are used for detecting surface defects. LiDAR scanners can collect high-quality 3D point cloud datasets. In order to automate the process of structural inspection, it is important to collect proper datasets and use an efficient approach to analyze them and find the defects. Deep Neural Networks (DNNs) have been recently used for detecting 3D objects within 3D point clouds. PointNet and PointNet++ are deep neural networks for classification, part segmentation, and semantic segmentation of point clouds that are modified and adapted in this work to detect surface concrete defects. The research contributions are: (1) Designing a LiDAR-equipped UAV platform for structural inspection using an affordable 2D scanner for data collection, and (2) Proposing a method for detecting concrete surface defects using deep neural networks based on LiDAR generated point clouds. Training and testing datasets are collected from four concrete bridges in Montréal and annotated manually. The point cloud dataset prepared in five areas, which contain more than 51 million points and 2,572 annotated defects in four classes of crack, light spalling, medium spalling, and severe spalling. The accuracies of 75% (adapted PointNet) and 79% (adapted PointNet++) in detecting defects are achieved in binary semantic segmentation.

Automation and Computational Intelligence for Road Maintenance and Management

Automation and Computational Intelligence for Road Maintenance and Management
Title Automation and Computational Intelligence for Road Maintenance and Management PDF eBook
Author Hamzeh Zakeri
Publisher John Wiley & Sons
Pages 548
Release 2022-06-22
Genre Computers
ISBN 1119800668

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Automation and Computational Intelligence for Road Maintenance and Management A comprehensive computational intelligence toolbox for solving problems in infrastructure management In Automation and Computational Intelligence for Road Maintenance and Management, a team of accomplished researchers delivers an incisive reference that covers the latest developments in computer technology infrastructure management. The book contains an overview of foundational and emerging technologies and methods in both automation and computational intelligence, as well as detailed presentations of specific methodologies. The distinguished authors emphasize the most recent advances in the maintenance and management of infrastructure robotics, automated inspection, remote sensing, and the applications of new and emerging computing technologies, including artificial intelligence, evolutionary computing, fuzzy logic, genetic algorithms, knowledge discovery and engineering, and more. Automation and Computational Intelligence for Road Maintenance and Management explores a universal synthesis of the cutting edge in parameters and indices to evaluate models. It also includes: Thorough introductions to management science and the latest methods of automation and the structure and framework of automation and computing intelligence Comprehensive explorations of advanced image processing techniques, recent advances in fuzzy, and diagnosis automation Practical discussions of segmentation and fragmentation and different types of features and feature extraction methods In-depth examinations of methods of classification along with various developed methodologies and models of quantification, evaluation, and indexing in automation Perfect for postgraduate students in road and transportation engineering, evaluation, and assessment, Automation and Computational Intelligence for Road Maintenance and Management will also earn a place in the libraries of researchers interested in or working with the evaluation and assessment of infrastructure.

An Evaluation of Surface Defect Detection in Reinforced Concrete Bridge Decks Using Terrestrial LiDAR

An Evaluation of Surface Defect Detection in Reinforced Concrete Bridge Decks Using Terrestrial LiDAR
Title An Evaluation of Surface Defect Detection in Reinforced Concrete Bridge Decks Using Terrestrial LiDAR PDF eBook
Author Ryan C. Hoensheid
Publisher
Pages 284
Release 2012
Genre
ISBN

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Image-based Condition Assessment for Concrete Bridge Inspection

Image-based Condition Assessment for Concrete Bridge Inspection
Title Image-based Condition Assessment for Concrete Bridge Inspection PDF eBook
Author Ram Sebak Adhikari
Publisher
Pages
Release 2014
Genre
ISBN

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EG-ICE 2020 Workshop on Intelligent Computing in Engineering

EG-ICE 2020 Workshop on Intelligent Computing in Engineering
Title EG-ICE 2020 Workshop on Intelligent Computing in Engineering PDF eBook
Author Ungureanu, Lucian Constantin
Publisher Universitätsverlag der TU Berlin
Pages 528
Release 2020-06-30
Genre Computers
ISBN 3798331553

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The 27th EG-ICE International Workshop 2020 brings together international experts working at the interface between advanced computing and modern engineering challenges. Many engineering tasks require open-world resolutions to support multi-actor collaboration, coping with approximate models, providing effective engineer-computer interaction, search in multi-dimensional solution spaces, accommodating uncertainty, including specialist domain knowledge, performing sensor-data interpretation and dealing with incomplete knowledge. While results from computer science provide much initial support for resolution, adaptation is unavoidable and most importantly, feedback from addressing engineering challenges drives fundamental computer-science research. Competence and knowledge transfer goes both ways. Der 27. Internationale EG-ICE Workshop 2020 bringt internationale Experten zusammen, die an der Schnittstelle zwischen fortgeschrittener Datenverarbeitung und modernen technischen Herausforderungen arbeiten. Viele ingenieurwissenschaftliche Aufgaben erfordern Open-World-Resolutionen, um die Zusammenarbeit mehrerer Akteure zu unterstützen, mit approximativen Modellen umzugehen, eine effektive Interaktion zwischen Ingenieur und Computer zu ermöglichen, in mehrdimensionalen Lösungsräumen zu suchen, Unsicherheiten zu berücksichtigen, einschließlich fachspezifischen Domänenwissens, Sensordateninterpretation durchzuführen und mit unvollständigem Wissen umzugehen. Während die Ergebnisse aus der Informatik anfänglich viel Unterstützung für die Lösung bieten, ist eine Anpassung unvermeidlich, und am wichtigsten ist, dass das Feedback aus der Bewältigung technischer Herausforderungen die computer-wissenschaftliche Grundlagenforschung vorantreibt. Kompetenz und Wissenstransfer gehen in beide Richtungen.