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

doi:10.1016/j.jobe.2020.101827

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 journal › Article › peer-review

446 Citations (SciVal)

Original language	English
Article number	101827
Journal	Journal of Building Engineering
Volume	32
DOIs	https://doi.org/10.1016/j.jobe.2020.101827
Publication status	Published (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.

Funders	Funder number
Engineering and Physical Sciences Research Council	EP/N509012/1
Innovate UK	104367, 10137

Keywords

Autoencoders
Construction industry
Convolutional neural networks
Deep learning
Generative adversarial networks

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10.1016/j.jobe.2020.101827

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@article{40f22920f65b4671b2c8e1e6b51e5348,

title = "Deep learning in the construction industry: A review of present status and future innovations",

keywords = "Autoencoders, Construction industry, Convolutional neural networks, Deep learning, Generative adversarial networks",

author = "Akinosho, \{Taofeek D.\} and Oyedele, \{Lukumon O.\} and Muhammad Bilal and Ajayi, \{Anuoluwapo O.\} and Delgado, \{Manuel Davila\} and Akinade, \{Olugbenga O.\} and Ahmed, \{Ashraf A.\}",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s)",

year = "2020",

month = nov,

doi = "10.1016/j.jobe.2020.101827",

language = "English",

volume = "32",

journal = "Journal of Building Engineering",

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T1 - Deep learning in the construction industry

T2 - A review of present status and future innovations

AU - Akinosho, Taofeek D.

AU - Oyedele, Lukumon O.

AU - Bilal, Muhammad

AU - Ajayi, Anuoluwapo O.

AU - Delgado, Manuel Davila

AU - Akinade, Olugbenga O.

AU - Ahmed, Ashraf A.

PY - 2020/11

Y1 - 2020/11

KW - Autoencoders

KW - Construction industry

KW - Convolutional neural networks

KW - Deep learning

KW - Generative adversarial networks

UR - https://www.scopus.com/pages/publications/85092169429

UR - https://www.scopus.com/pages/publications/85092169429#tab=citedBy

U2 - 10.1016/j.jobe.2020.101827

DO - 10.1016/j.jobe.2020.101827

M3 - Article

AN - SCOPUS:85092169429

VL - 32

JO - Journal of Building Engineering

JF - Journal of Building Engineering

M1 - 101827

ER -

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

Funding

Keywords

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