| Survey of Quantization Techniques for On-Device Vision-based Crack Detection | Feb 4, 2025 | QuantizationStructural Health Monitoring | —Unverified | 0 |
| FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM | Jan 31, 2025 | Computational EfficiencyCrack Segmentation | —Unverified | 0 |
| Vision-based autonomous structural damage detection using data-driven methods | Jan 28, 2025 | Structural Health Monitoring | —Unverified | 0 |
| Automatic selection of the best neural architecture for time series forecasting via multi-objective optimization and Pareto optimality conditions | Jan 21, 2025 | State Space ModelsStructural Health Monitoring | —Unverified | 0 |
| Data-driven Detection and Evaluation of Damages in Concrete Structures: Using Deep Learning and Computer Vision | Jan 21, 2025 | Instance SegmentationSegmentation | —Unverified | 0 |
| On the use of Statistical Learning Theory for model selection in Structural Health Monitoring | Jan 14, 2025 | Learning TheoryModel Selection | —Unverified | 0 |
| Automated Detection and Analysis of Minor Deformations in Flat Walls Due to Railway Vibrations Using LiDAR and Machine Learning | Jan 11, 2025 | Structural Health Monitoring | —Unverified | 0 |
| CrackESS: A Self-Prompting Crack Segmentation System for Edge Devices | Dec 10, 2024 | Computational EfficiencyCrack Segmentation | —Unverified | 0 |
| MSCrackMamba: Leveraging Vision Mamba for Crack Detection in Fused Multispectral Imagery | Dec 9, 2024 | Image SegmentationMamba | —Unverified | 0 |
| Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data | Dec 5, 2024 | Anomaly DetectionSelf-Supervised Learning | —Unverified | 0 |
