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What is Structural Health Monitoring 2025 about?
This study presents a deep learning-based system for real-time crack detection and prediction in structural health monitoring, achieving 98.88% precision through a model that integrates CNN, VGG16, U-Net, and Swin Transformer architectures. The proposed method enhances crack classification and segmentation while addressing issues like data imbalance and generalization, ultimately contributing to preventive maintenance and infrastructure safety. The research highlights the effectiveness of automated monitori
- Author
- 99999111222
- Language
- EN