[HTML][HTML] Deep learning in the construction industry: A review of present status and future innovations
The construction industry is known to be overwhelmed with resource planning, risk
management and logistic challenges which often result in design defects, project delivery …
management and logistic challenges which often result in design defects, project delivery …
Towards big data driven construction industry
The construction industry is currently going through an intelligent revolution. The profound
transformation of the Industry 4.0 era is made possible by contemporary technologies such …
transformation of the Industry 4.0 era is made possible by contemporary technologies such …
Self-supervised learning for electroencephalography
Decades of research have shown machine learning superiority in discovering highly
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
nonlinear patterns embedded in electroencephalography (EEG) records compared with …
Graph neural network and reinforcement learning for multi‐agent cooperative control of connected autonomous vehicles
A connected autonomous vehicle (CAV) network can be defined as a set of connected
vehicles including CAVs that operate on a specific spatial scope that may be a road network …
vehicles including CAVs that operate on a specific spatial scope that may be a road network …
Automatic detection method of cracks from concrete surface imagery using two‐step light gradient boosting machine
Automated crack detection based on image processing is widely used when inspecting
concrete structures. The existing methods for crack detection are not yet accurate enough …
concrete structures. The existing methods for crack detection are not yet accurate enough …
Learning dynamic and hierarchical traffic spatiotemporal features with transformer
Traffic forecasting has attracted considerable attention due to its importance in proactive
urban traffic control and management. Scholars and engineers have exerted considerable …
urban traffic control and management. Scholars and engineers have exerted considerable …
Iterative application of generative adversarial networks for improved buried pipe detection from images obtained by ground‐penetrating radar
PJ Chun, M Suzuki, Y Kato - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Ground‐penetrating radar (GPR) is widely used to determine the location of buried pipes
without excavation, and machine learning has been researched to automatically identify the …
without excavation, and machine learning has been researched to automatically identify the …
A deep learning‐based image captioning method to automatically generate comprehensive explanations of bridge damage
Photographs of bridges can reveal considerable technical information such as the part of the
structure that is damaged and the type of damage. Maintenance and inspection engineers …
structure that is damaged and the type of damage. Maintenance and inspection engineers …
Comparison of neural network, Gaussian regression, support vector machine, long short-term memory, multi-gene genetic programming, and M5 Trees methods for …
In this study, it was investigated that how machine learning (ML) methods show performance
in different problems having different characteristics. Six ML approaches including Artificial …
in different problems having different characteristics. Six ML approaches including Artificial …
Data mining in the construction industry: Present status, opportunities, and future trends
H Yan, N Yang, Y Peng, Y Ren - Automation in Construction, 2020 - Elsevier
The construction industry is experiencing remarkable growth in the data generation. Data
mining (DM) from considerable amount of data in the construction industry has emerged as …
mining (DM) from considerable amount of data in the construction industry has emerged as …