Meijing Tan
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
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Research Areas
Biomedical Subjects
Biography and Research Information
OverviewAI-generated summary
Meijing Tan's research encompasses a range of topics, including the psychometric validation of health-related scales and the application of advanced imaging and machine learning techniques. Tan has contributed to studies on adolescent attitudes towards dementia, including the translation and validation of a Chinese version of the Brief Adolescent Attitudes Towards Dementia Scale. Additionally, Tan's work involves developing vision-based frameworks for leakage detection in building systems, utilizing attention-enhanced deep neural networks and unmanned aerial vehicles. Other research areas include physics-and image-informed reliability prediction for pipelines and hybrid quantum annealing for exam scheduling.
Metrics
- h-index: 1
- Publications: 7
- Citations: 5
Selected Publications
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A vision-based leakage detection framework for roof systems using attention-enhanced deep neural networks (2026)
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Physics-and Image-Informed Reliability Prediction for Pipelines Under Competing Failure Modes (2026)
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Adaptive Vision-based Methods for Building Anomaly Detection Using Unmanned Aerial Vehicles and Machine Learning (2025)Journal of the Arkansas Academy of Science OpenAlex
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An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems (2025)
Collaboration Network
Top Collaborators
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- A vision-based leakage detection framework for roof systems using attention-enhanced deep neural networks
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- An Attention-Enhanced YOLOv8 Architecture for Leakage Detection in Building Systems
- Physics-and Image-Informed Reliability Prediction for Pipelines Under Competing Failure Modes
- Physics-and Image-Informed Reliability Prediction for Pipelines Under Competing Failure Modes
- A vision-based leakage detection framework for roof systems using attention-enhanced deep neural networks
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