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      Deep learning–based nondestructive evaluation of reinforcement bars using ground-penetrating radar and electromagnetic induction data

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      Li_etal_CCIE_deep_learning_based_AAM (7.340Mb)
      Publication date
      15/11/2022
      Author
      Li, Xiaofeng
      Liu, Hai
      Zhou, Feng
      Chen, Zhongchang
      Giannakis, Iraklis
      Slob, Evert
      Metadata
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      Citation
      Li , X , Liu , H , Zhou , F , Chen , Z , Giannakis , I & Slob , E 2022 , ' Deep learning–based nondestructive evaluation of reinforcement bars using ground-penetrating radar and electromagnetic induction data ' , Computer-Aided Civil and Infrastructure Engineering , vol. 37 , no. 14 , pp. 1834-1853 . https://doi.org/10.1111/mice.12798
      URI
      https://hdl.handle.net/2164/19620
      DOI
      https://doi.org/10.1111/mice.12798
      Rights
      This is the peer reviewed version of the article which has been published in final form at https://doi.org/10.1111/mice.12798. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.
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