The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Automated construction progress measurement using a 4D building information model and 3D data
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Citations
Cites
Wu, Y. (1999) · Technometrics · doi:10.1080/00401706.1999.10485951 · Cited by 27,221
A method for registration of 3-D shapes
Besl, P. J., & McKay, N. D. (1992) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.121791 · Cited by 18,103
Robust registration of 2D and 3D point sets
Fitzgibbon, A. W. (2003) · Image and Vision Computing · doi:10.1016/j.imavis.2003.09.004 · Cited by 925
Credit scoring with a data mining approach based on support vector machines
Huang, C.-L., Chen, M.-C., & Wang, C.-J. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2006.07.007 · Cited by 804
Bosché, F. (2010) · Advanced Engineering Informatics · doi:10.1016/j.aei.2009.08.006 · Cited by 482
Natural terrain classification using three‐dimensional ladar data for ground robot mobility
Lalonde, J., Vandapel, N., Huber, D. F., & Hebert, M. (2006) · Journal of Field Robotics · doi:10.1002/rob.20134 · Cited by 464
Golparvar-Fard, M., Peña-Mora, F., & Savarese, S. (2015) · Journal of Computing in Civil Engineering · doi:10.1061/(asce)cp.1943-5487.0000205 · Cited by 404
Automated progress tracking using 4D schedule and 3D sensing technologies
Turkan, Y., Bosche, F., Haas, C. T., & Haas, R. (2012) · Automation in Construction · doi:10.1016/j.autcon.2011.10.003 · Cited by 374
Widodo, A., Yang, B.-S., & Han, T. (2007) · Expert Systems with Applications · doi:10.1016/j.eswa.2005.11.031 · Cited by 296
Forecasting financial condition of Chinese listed companies based on support vector machine
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Cited by
Computer vision techniques in construction: A critical review
Xu, S., Wang, J., Shou, W., Ngo, T., Sadick, A.-M., & Wang, X. (2021) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09504-3 · Cited by 409
Patterns and trends in Building Information Modeling (BIM) research: A Latent Semantic Analysis
Yalcinkaya, M., & Singh, V. (2015) · Automation in Construction · doi:10.1016/j.autcon.2015.07.012 · Cited by 272
Han, K. K., & Golparvar-Fard, M. (2015) · Automation in Construction · doi:10.1016/j.autcon.2015.02.007 · Cited by 246
GPT models in construction industry: Opportunities, limitations, and a use case validation
Saka, A., Taiwo, R., Saka, N., Salami, B. A., Ajayi, S., Akande, K., & Kazemi, H. (2024) · Developments in the Built Environment · doi:10.1016/j.dibe.2023.100300 · Cited by 202
Material Recognition for Automated Progress Monitoring using Deep Learning Methods
Mahami, H., Ghassemi, N., Darbandy, M. T., Shoeibi, A., Hussain, S., Nasirzadeh, F., Alizadehsani, R., Nahavandi, D., Khosravi, A., & Nahavandi, S. (2020) · arXiv · doi:10.48550/arxiv.2006.16344 · Cited by 25
Metadata
- Authors
- Kim, C., Son, H., & Kim, C.
- Venue
- Automation in Construction
- Publisher
- Elsevier BV
- Published
- 2013-05
- Volume
- 31
- Pages
- 75-82
- ISSN
- 0926-5805 (ISSN-L)
- OpenAlex
- W2027285680
- Cited by
- 317
- References
- 23
- FWCI
- 27.35
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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- CoChat. (2026). Citation check: Automated construction progress measurement using a 4D building information model and 3D data. https://app.cochat.ai/papers/10.1016/j.autcon.2012.11.041
- The paper
- Kim, C., Son, H., & Kim, C. (2013). Automated construction progress measurement using a 4D building information model and 3D data. Automation in Construction. https://doi.org/10.1016/j.autcon.2012.11.041
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
