Keyphrases
Surface Crack
100%
Automated Detection
100%
Union Model
100%
Global Attention
100%
Attention Module
100%
YOLOv5
100%
Intersection over Union
100%
Bridge Surface
100%
Hong Kong
50%
F1 Score
50%
Reinforced Concrete Bridges
50%
Precision-recall
50%
Rapid Growth
25%
Traffic Volume
25%
Defect Type
25%
Inference Process
25%
Training Process
25%
Dense Urban Areas
25%
Generalization Ability
25%
Computational Cost
25%
Human Safety
25%
Crack Detection
25%
Deployable
25%
Traffic Density
25%
Loss Function
25%
Forgoing
25%
Visual Inspection
25%
Complex Background
25%
Non-uniform Environment
25%
Bridge Inspection
25%
Mean Average Precision
25%
Neural Network Structure
25%
Random Characteristic
25%
Labor-intensiveness
25%
Deep Learning Model
25%
Convolutional Neural Network
25%
Vehicle Load
25%
Training Costs
25%
Diverse Tasks
25%
Evaluation Metrics
25%
Multi-target Detection
25%
Background Texture
25%
Two-stage Deep Learning
25%
Computer Vision Models
25%
Detection Head
25%
Traffic Vehicle
25%
Bridge Crack Detection
25%
Hazardousness
25%
Decoupled Head
25%
Test Precision
25%
Visual Inspection Method
25%
Regular Bridge
25%
Concrete Bridge Crack
25%
Engineering
Surface Crack
100%
Concrete Bridges
100%
Bridge Surface
100%
Visual Inspection
66%
Crack Detection
66%
Reinforced Concrete
66%
Computervision
33%
Multiscale
33%
Traffic Volume
33%
Fundamental Component
33%
Inference Process
33%
Human Safety
33%
Mean Score
33%
Inspection Method
33%
Limitations
33%
Metrics
33%
Loss Function
33%
Computational Cost
33%
Deep Learning Method
33%
Convolutional Neural Network
33%
Computer Science
YOLO
100%
Visual Inspection
66%
Deep Learning Model
33%
Convolutional Neural Network
33%
Generalization Ability
33%
Neural Network Architecture
33%
Object Detection
33%
Evaluation Metric
33%
Mean Average Precision
33%
Training Process
33%
Computational Cost
33%
Fundamental Component
33%
Inspection Method
33%
Inference Process
33%
Computer Vision
33%
Material Science
Reinforced Concrete
100%
Surface Crack
100%
Crack Detection
100%
Density
50%