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Vision-based monitoring of railway superstructure: A review
Peyman Aela
, Jiafu Cai
, Guoqing Jing
,
Hung Lin Chi
Department of Building and Real Estate
The Hong Kong Polytechnic University
Research output
:
Journal article publication
›
Review article
›
Academic research
›
peer-review
33
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Citations (Scopus)
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Dive into the research topics of 'Vision-based monitoring of railway superstructure: A review'. Together they form a unique fingerprint.
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Keyphrases
Vision-based Monitoring
100%
Railway Superstructure
100%
Railway Track
66%
Computer Vision-based
66%
Maintenance Requirement
33%
Catenary System
33%
Fastening System
33%
Machine Learning Techniques
33%
Visual Data
33%
System Support
33%
Sleeper
33%
Vision-based
33%
Track Stability
33%
Track Condition
33%
Machine Learning Approach
33%
Computer Vision Applications
33%
Camera Sensor
33%
Railway Engineering
33%
Automated Assessment
33%
Advanced Image Processing
33%
Computer Vision Techniques
33%
Computer Vision Algorithms
33%
System Layer
33%
Ballast Layer
33%
Track Maintenance
33%
Rail Profile
33%
Rail Surface
33%
Recent Advancements
33%
Camera Drone
33%
Railway Track Engineering
33%
Engineering
Railway
100%
Superlattice
100%
Computervision
57%
Engineering
28%
Potential Application
14%
Learning Approach
14%
Drone
14%
Applicability
14%
Stability Condition
14%
Fastening System
14%
Ballast Layer
14%
Image Processing
14%
Limitations
14%
Support System
14%
Machine Learning Technique
14%
Rail Surface
14%
Learning System
14%
Computer Science
Computer Vision
100%
Machine Learning Approach
33%
Machine Learning Technique
33%
Research Direction
33%
Image Processing
33%
Computer Vision Algorithms
33%
Potential Application
33%
Stability Condition
33%
Earth and Planetary Sciences
Computer Vision
100%
Machine Learning
50%
Support System
25%
Image Processing
25%
Chemical Engineering
Learning System
100%