Deep Learning–Based Automated Generation of Material Data with Object–Space Relationships for Scan to BIM-Reference-Cited by-同舟云学术

Deep Learning–Based Automated Generation of Material Data with Object–Space Relationships for Scan to BIM

Published:2023-05 Issue:3 Volume:39 Page:
ISSN:0742-597X
Container-title:Journal of Management in Engineering
language:en
Short-container-title:J. Manage. Eng.

Author:

Kim Sohyun¹,Jeong Kwangbok²^ORCID,Hong Taehoon³^ORCID,Lee Jaehong⁴,Lee Jaewook⁵^ORCID

Affiliation:

1. Graduate Research Assistant, Dept. of Architectural Engineering, Sejong Univ., Seoul 05006, Republic of Korea.

2. Assistant Professor, Deep Learning Architecture Research Center, Dept. of Architectural Engineering, Sejong Univ., Seoul 05006, Republic of Korea. ORCID: .

3. Underwood Distinguished Professor, Dept. of Architecture and Architectural Engineering, Yonsei Univ., Seoul 03722, Republic of Korea. ORCID: .

4. Professor, Deep Learning Architecture Research Center, Dept. of Architectural Engineering, Sejong Univ., Seoul 05006, Republic of Korea.

5. Professor, Deep Learning Architecture Research Center, Department of Architectural Engineering, Sejong Univ., Seoul 05006, Republic of Korea (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management Science and Operations Research,Strategy and Management,General Engineering,Industrial relations,Building and Construction

Link

https://ascelibrary.org/doi/pdf/10.1061/JMENEA.MEENG-5143

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3. Armeni I. O. Sener A. R. Zamir H. Jiang I. Brilakis M. Fischer and S. Savarese. 2016. “3D semantic parsing of large-scale indoor spaces.” In Proc. IEEE Conf. on Computer Vision and Pattern Recognition 1534–1543. New York: IEEE. https://doi.org/10.1109/CVPR.2016.170.

4. Analysis of K-Means and K-Medoids Algorithm For Big Data

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