Deep learning in the construction industry: A review of present status and future innovations

Taofeek D. Akinosho, Lukumon O. Oyedele*, Muhammad Bilal, Anuoluwapo O. Ajayi, Manuel Davila Delgado, Olugbenga O. Akinade, Ashraf A. Ahmed

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    272 Citations (SciVal)
    Original languageEnglish
    Article number101827
    JournalJournal of Building Engineering
    Volume32
    DOIs
    Publication statusPublished (VoR) - Nov 2020

    Funding

    The authors would like to express their sincere gratitude to Innovate UK (Grant Application No 10137 and File No 104367 ) and EPSRC (Grant Ref No EP/N509012/1 ) for providing the financial support for this study.

    FundersFunder number
    Engineering and Physical Sciences Research CouncilEP/N509012/1
    Innovate UK104367, 10137

      Keywords

      • Autoencoders
      • Construction industry
      • Convolutional neural networks
      • Deep learning
      • Generative adversarial networks

      Fingerprint

      Dive into the research topics of 'Deep learning in the construction industry: A review of present status and future innovations'. Together they form a unique fingerprint.

      Cite this