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  • Enhancing visual-based bridge condition assessment for concrete crack evaluation using image processing techniques

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    WiPUB2148.pdf (202.0Kb)
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    Version of Record (VoR)
    Author(s)
    Wi, H
    Nguyen, V
    Lee, J
    Guan, H
    Loo, YC
    Blumenstein, M
    Griffith University Author(s)
    Loo, Yew-Chaye
    Guan, Hong
    Year published
    2013
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    Abstract
    Condition assessment is one of the most essential practices in bridge asset management to maintain the safety and durability of structures. Routine bridge inspection, a visual-based method, is regularly performed by qualified inspectors to determine the condition of individual bridge elements manually using bridge inspection standards. However, the quality of a visual-based condition assessment relies heavily on the inspector's knowledge and experience. The research presented here focuses on the development of an enhanced method to minimise the shortcomings of visual-based inspection. In this paper, we investigate the ...
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    Condition assessment is one of the most essential practices in bridge asset management to maintain the safety and durability of structures. Routine bridge inspection, a visual-based method, is regularly performed by qualified inspectors to determine the condition of individual bridge elements manually using bridge inspection standards. However, the quality of a visual-based condition assessment relies heavily on the inspector's knowledge and experience. The research presented here focuses on the development of an enhanced method to minimise the shortcomings of visual-based inspection. In this paper, we investigate the performance of RBF-kernel support vector machines (SVMs), a supervised machine learning technique, to increase the reliability of visual-based bridge inspection. The results of this study can contribute to minimising the shortcomings of current visual-based bridge inspection practices.
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    Journal Title
    IABSE Symposium Report
    Volume
    101
    Issue
    1
    Publisher URI
    https://iabse.org/Publications/Reports
    Copyright Statement
    © 2013 IABSE. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.
    Subject
    Civil engineering not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/336448
    Collection
    • Journal articles

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