State-of-the-art on research and applications of machine learning in the building life cycle

T Hong, Z Wang, X Luo, W Zhang - Energy and Buildings, 2020 - Elsevier
Fueled by big data, powerful and affordable computing resources, and advanced algorithms,
machine learning has been explored and applied to buildings research for the past decades …

Construction performance monitoring via still images, time-lapse photos, and video streams: Now, tomorrow, and the future

J Yang, MW Park, PA Vela, M Golparvar-Fard - Advanced Engineering …, 2015 - Elsevier
Timely and accurate monitoring of onsite construction operations can bring an immediate
awareness on project specific issues. It provides practitioners with the information they need …

[HTML][HTML] Building information modelling, artificial intelligence and construction tech

R Sacks, M Girolami, I Brilakis - Developments in the Built Environment, 2020 - Elsevier
Adoption of digital information tools in the construction sector provides fertile ground for the
birth and growth of companies that specialize in applications of technologies to design and …

Detecting construction equipment using a region-based fully convolutional network and transfer learning

H Kim, H Kim, YW Hong, H Byun - Journal of computing in Civil …, 2018 - ascelibrary.org
For proper construction site management and plan revisions during construction, it is
necessary to understand a construction site's status in real time. Many vision-based …

Combining inverse photogrammetry and BIM for automated labeling of construction site images for machine learning

A Braun, A Borrmann - Automation in Construction, 2019 - Elsevier
Image-based object detection provides a valuable basis for site information retrieval and
construction progress monitoring. Machine learning approaches, such as neural networks …

Appearance-based material classification for monitoring of operation-level construction progress using 4D BIM and site photologs

KK Han, M Golparvar-Fard - Automation in construction, 2015 - Elsevier
This paper presents a new appearance-based material classification method for monitoring
construction progress deviations at the operational-level. The method leverages 4D Building …

[PDF][PDF] Recognizing diverse construction activities in site images via relevance networks of construction-related objects detected by convolutional neural networks

X Luo, H Li, D Cao, F Dai, JO Seo, SH Lee - J. Comput. Civ. Eng, 2018 - researchgate.net
Timely and overall knowledge of the states and resource allocation of diverse activities on
construction sites is critical to resource leveling, progress tracking, and productivity analysis …

Self-supervised material and texture representation learning for remote sensing tasks

P Akiva, M Purri, M Leotta - … of the IEEE/CVF Conference on …, 2022 - openaccess.thecvf.com
Self-supervised learning aims to learn image feature representations without the usage of
manually annotated labels. It is often used as a precursor step to obtain useful initial network …

Vision-based material recognition for automated monitoring of construction progress and generating building information modeling from unordered site image …

A Dimitrov, M Golparvar-Fard - Advanced Engineering Informatics, 2014 - Elsevier
Automatically monitoring construction progress or generating Building Information Models
using site images collections–beyond point cloud data–requires semantic information such …

Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs

M Golparvar-Fard, F Peña-Mora… - Journal of computing …, 2009 - ascelibrary.org
The ability to effectively communicate progress information and represent as-built and as-
planned progress discrepancies are identified as key components for successful project …