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Structural Health Monitoring
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Structural Vibration Monitoring with Diffractive Optical Processors
Mechanical in-sensor computing: a programmable meta-sensor for structural damage classification without external electronic power
Bridging the Reality Gap in Digital Twins with Context-Aware, Physics-Guided Deep Learning
Localization of Impacts on Thin-Walled Structures by Recurrent Neural Networks: End-to-end Learning from Real-World Data
On-Device Crack Segmentation for Edge Structural Health Monitoring
Fault Diagnosis of 3D-Printed Scaled Wind Turbine Blades
Data-Driven Structural State Estimation via Multi-Fidelity Gaussian Process Models
Guided Wave-Based Structural Awareness Under Varying Operating States via Manifold Representations
Towards a Universal Vibration Analysis Dataset: A Framework for Transfer Learning in Predictive Maintenance and Structural Health Monitoring
A Geometric-Aware Perspective and Beyond: Hybrid Quantum-Classical Machine Learning Methods
An optimal baseline selection methodology for data-driven damage detection and temperature compensation in acousto-ultrasonics
Active management of battery degradation in wireless sensor network using deep reinforcement learning for group battery replacement
Efficient dynamic modal load reconstruction using physics-informed Gaussian processes based on frequency-sparse Fourier basis functions
Real-Time Structural Deflection Estimation in Hydraulically Actuated Systems Using 3D Flexible Multibody Simulation and DNNs
Survey of Quantization Techniques for On-Device Vision-based Crack Detection
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM
Vision-based autonomous structural damage detection using data-driven methods
Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision
Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions
On the use of Statistical Learning Theory for model selection in Structural Health Monitoring
Automated Detection and Analysis of Minor Deformations in Flat Walls Due to Railway Vibrations Using LiDAR and Machine Learning
CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices
MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery
Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data
Signal-based online acceleration and strain data fusion using B-splines and Kalman filter for full-field dynamic displacement estimation
When does a bridge become an aeroplane?
NonSysId: A nonlinear system identification package with improved model term selection for NARMAX models
Comparison of Tiny Machine Learning Techniques for Embedded Acoustic Emission Analysis
Deep Learning for Micro-Scale Crack Detection on Imbalanced Datasets Using Key Point Localization
Multi-temporal crack segmentation in concrete structure using deep learning approaches
Deep Learning-Based Fatigue Cracks Detection in Bridge Girders using Feature Pyramid Networks
Addressing the Pitfalls of Image-Based Structural Health Monitoring: A Focus on False Positives, False Negatives, and Base Rate Bias
Multi-input Multi-output Loewner Framework for Vibration-based Damage Detection on a Trainer Jet
Very High-Resolution Bridge Deformation Monitoring Using UAV-based Photogrammetry
Deep learning-based Visual Measurement Extraction within an Adaptive Digital Twin Framework from Limited Data Using Transfer Learning
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