Deep Learning in Construction: Review of Applications and Potential Avenues-Reference-Cited by-同舟云学术

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Deep Learning in Construction: Review of Applications and Potential Avenues

Published:2022-03 Issue:2 Volume:36 Page:
ISSN:0887-3801
Container-title:Journal of Computing in Civil Engineering
language:en
Short-container-title:J. Comput. Civ. Eng.

Author:

Jacobsen Emil L.¹^ORCID,Teizer Jochen²^ORCID

Affiliation:

1. Ph.D. Student, Dept. of Civil and Architectural Engineering, Aarhus Univ., Aarhus C 8000, Denmark (corresponding author). ORCID: .

2. Associate Professor, Dept. of Civil and Architectural Engineering, Aarhus Univ., Aarhus C 8000, Denmark. ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Computer Science Applications,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29CP.1943-5487.0001010

Reference87 articles.

1. Estimating Preconstruction Services for Bridge Design Projects

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

3. Modeling dynamic construction work template from existing scheduling records via sequential machine learning

4. Critical success factors for implementing building information modelling (BIM): A longitudinal review

5. AN INTEGRATED WEB-BASED DATA WAREHOUSE AND ARTIFICIAL NEURAL NETWORKS SYSTEM FOR UNIT PRICE ANALYSIS WITH INFLATION ADJUSTMENT / INTEGRUOTA INTERNETINĖ DUOMENŲ SAUGYKLOS IR DIRBTINIŲ NEURONINIŲ TINKLŲ SISTEMA, SKIRTA VIENETO KAINAI ANALIZUOTI ATSIŽVELGIANT Į INFLIACIJĄ

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4. Estimating Solar Energy within the scope of environmental factors by the Neural Network algorithm;Mühendislik Bilimleri ve Araştırmaları Dergisi;2024-04-30

5. Development of an action classification method for construction sites combining pose assessment and object proximity evaluation;Journal of Ambient Intelligence and Humanized Computing;2024-03-05

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