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Bayesian multi-task learning methodology for reconstruction of structural health monitoring data
Free accessSAGE Publications | 2019| -
Computer vision and deep learning–based data anomaly detection method for structural health monitoring
SAGE Publications | 2019| -
A review of computer vision–based structural health monitoring at local and global levels
SAGE Publications | 2021| -
Data fusion approaches for structural health monitoring and system identification: Past, present, and future
SAGE Publications | 2020| -
Optimization of sensor placement for structural health monitoring: a review
SAGE Publications | 2019| -
A novel deep learning-based method for damage identification of smart building structures
SAGE Publications | 2019| -
Evaluation of deep learning approaches based on convolutional neural networks for corrosion detection
SAGE Publications | 2018| -
Structural health monitoring: Closing the gap between research and industrial deployment
Free accessSAGE Publications | 2018| -
Crack and Noncrack Classification from Concrete Surface Images Using Machine Learning
SAGE Publications | 2019| -
Computational methodologies for optimal sensor placement in structural health monitoring: A review
SAGE Publications | 2020| -
Machine learning and structural health monitoring overview with emerging technology and high-dimensional data source highlights
Free accessSAGE Publications | 2022| -
Analysis of barely visible impact damage severity with ultrasonic guided Lamb waves
SAGE Publications | 2020|
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