Deep Learning for Earthquake Disaster Assessment: Objects, Data, Models, Stages, Challenges, and Opportunities
J Jia, W Ye - Remote Sensing, 2023 - mdpi.com
Earthquake Disaster Assessment (EDA) plays a critical role in earthquake disaster
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
prevention, evacuation, and rescue efforts. Deep learning (DL), which boasts advantages in …
Concrete dam damage detection and localisation based on YOLOv5s-HSC and photogrammetric 3D reconstruction
S Zhao, F Kang, J Li - Automation in Construction, 2022 - Elsevier
This paper presents a system for detecting damages in concrete dams that combines the
proposed YOLOv5s-HSC algorithm and a three-dimensional (3D) photogrammetric …
proposed YOLOv5s-HSC algorithm and a three-dimensional (3D) photogrammetric …
Convolutional neural networks (CNNs)-based multi-category damage detection and recognition of high-speed rail (HSR) reinforced concrete (RC) bridges using test …
The fast networking of high-speed rail (HSR) may cause in-service fatigue and ultimate load
damage to bridges. This paper investigates the application of deep convolutional neural …
damage to bridges. This paper investigates the application of deep convolutional neural …
Real‐time automatic crack detection method based on drone
Real‐time automated drone‐based crack detection can be used for efficient building
damage assessment. This paper proposes an automated real‐time crack detection method …
damage assessment. This paper proposes an automated real‐time crack detection method …
[HTML][HTML] Classification and Application of Deep Learning in Construction Engineering and Management–A Systematic Literature Review and Future Innovations
Q Li, Y Yang, G Yao, F Wei, R Li, M Zhu… - Case Studies in …, 2024 - Elsevier
In the ever-evolving landscape of construction engineering and management (CEM), the
dynamic and unique characteristics of construction project environments constantly present …
dynamic and unique characteristics of construction project environments constantly present …
Image-based reinforced concrete component mechanical damage recognition and structural safety rapid assessment using deep learning with frequency information
Safety assessment of post-event damaged structures is vital and significant because it
directly affects life security, structural repair, and economic loss, especially in earthquakes …
directly affects life security, structural repair, and economic loss, especially in earthquakes …
A graph‐based method for quantifying crack patterns on reinforced concrete shear walls
This paper presents an innovative method to quantify damage based on surface cracks of
reinforced concrete shear walls (RCSWs). The key idea is to use artificial intelligence and …
reinforced concrete shear walls (RCSWs). The key idea is to use artificial intelligence and …
Bidirectional graphics-based digital twin framework for quantifying seismic damage of structures using deep learning networks
Tremendous effort has been devoted toward develo** automated post-earthquake
inspection techniques, including automated image collection and damage identification …
inspection techniques, including automated image collection and damage identification …
UAV imagery based potential safety hazard evaluation for high-speed railroad using Real-time instance segmentation
Potential safety hazards (PSHs) along the track needs to be inspected and evaluated
regularly to ensure a safe environment for high-speed railroad operations. Other than track …
regularly to ensure a safe environment for high-speed railroad operations. Other than track …
Detection of damages caused by earthquake and reinforcement corrosion in RC buildings with Deep Transfer Learning
Abstract The Reinforced Concrete (RC) buildings in countries within earthquake zones like
Turkey are generally damaged more than anticipated during earthquakes. Corrosion of …
Turkey are generally damaged more than anticipated during earthquakes. Corrosion of …