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[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 …
Pre-owned housing price index forecasts using Gaussian process regressions
B **, X Xu - Journal of Modelling in Management, 2024 - emerald.com
Purpose The purpose of this study is to make property price forecasts for the Chinese
housing market that has grown rapidly in the last 10 years, which is an important concern for …
housing market that has grown rapidly in the last 10 years, which is an important concern for …
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 …
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 …
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 …
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 …
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 …
Transformer‐optimized generation, detection, and tracking network for images with drainage pipeline defects
Regular detection of defects in drainage pipelines is crucial. However, some problems
associated with pipeline defect detection, such as data scarcity and defect counting difficulty …
associated with pipeline defect detection, such as data scarcity and defect counting difficulty …