..., the integration of deep learning–based component detection with NURBS-based reconstruction workflows in Grasshopper has received limited attention. This study presents an integrated plugin workflow that detects interior components in scanned environments and reconstructs them as parametric NURBS-based models...

... and efficiency. Originality/value This paper integrates deep learning with an improved optimization algorithm to present an integrated solution for one - step road crack repair. Songtao Lv can be contacted at: lst@csust.edu.cn 05 06 2025 10 02 2026 17 03 2026 © Emerald Publishing...

..., and viewpoints. Each image was annotated with detailed captions, resulting in over 65,000 descriptions. The dataset’s diversity and richness were statistically analyzed. Additionally, three widely used deep learning-based image captioning models were evaluated on the dataset to assess its applicability...

... metrics and latency, considering the practice in construction applications. Findings The deep learning models achieve mean average precision (mAP) ranging from 0.856 to 0.94 for 3D worker detection. The best detection performance is achieved when applying 3D convolutional neural networks to voxel data...

... 2024 17 03 2024 18 04 2024 22 05 2024 © Emerald Publishing Limited 2024 Emerald Publishing Limited Licensed re-use rights only Automation Road construction Construction progress monitoring Deep learning Sensor UGV LSTM Currently, it is estimated that road...

...Mikias Gugssa; Long Li; Lina Pu; Ali Gurbuz; Yu Luo; Jun Wang Purpose Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated...

... in the field of architecture and fire protection, and then the ontology of these elements is developed. Based on this, a building standard corpus is built, and deep learning models are trained to automatically label the building standard texts. The Neo4j is utilized for knowledge graph construction and storage...

... performance. Design/methodology/approach This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features...

... to propose an intelligent method to detect construction project contract missing clauses based on Natural Language Processing (NLP) and deep learning technology. Design/methodology/approach A complete classification scheme of contract clauses is designed based on NLP. First, construction contract texts...

... a video monitoring method to evaluate the working state of a tower crane. Yang et al. (2019) successfully identified the safe distance between the hook and the worker by using a monitoring camera installed on the tower crane. Deep learning Object detection Faster R-CNN Computer...

...Youjin Jang; Inbae Jeong; Yong K. Cho Purpose The study seeks to identify the impact of variables in a deep learning-based bankruptcy prediction model, which has achieved superior performance to other prediction models but cannot easily interpret hidden processes. Design/methodology/approach...

... in construction (ICTC). The fundamental problem is that ICTC incorporates various techniques and thus cannot be simply represented by man-made queries. To investigate this concern, this study develops a binary classifier by utilizing deep learning and NLP techniques to automatically identify whether a patent...