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Structural Health Monitoring

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Showing 1–25 of 197 papers

TitleStatusHype
Digital twin for virtual sensing of ferry quays via a Gaussian Process Latent Force Model—0
Structural Vibration Monitoring with Diffractive Optical Processors—0
Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power—0
Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning—0
Localization of Impacts on Thin-Walled Structures by Recurrent Neural Networks: End-to-end Learning from Real-World Data—0
On-Device Crack Segmentation for Edge Structural Health Monitoring—0
Fault Diagnosis of 3D-Printed Scaled Wind Turbine Blades—0
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models—0
Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring—0
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations—0
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods—0
An optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics—0
Active management of battery degradation in wireless sensor network using deep reinforcement learning for group battery replacement—0
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functionsCode0
Real-Time Structural Deflection Estimation in Hydraulically Actuated Systems Using 3D Flexible Multibody Simulation and DNNs—0
Survey of Quantization Techniques for On-Device Vision-based Crack Detection—0
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM—0
Vision-based autonomous structural damage detection using data-driven methods—0
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions—0
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision—0
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring—0
Automated Detection and Analysis of Minor Deformations in Flat Walls Due to Railway Vibrations Using LiDAR and Machine Learning—0
CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices—0
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery—0
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data—0
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