A5039393749- Asphalt Pavement Performance Evaluation
- Infrastructure Maintenance and Monitoring
- Industrial Vision Systems and Defect Detection
- Non-Destructive Testing Techniques
- Concrete Corrosion and Durability
Oklahoma State University Oklahoma City
2022-2023
Oklahoma State University
2023
Pixel-level detection of expansion joints on complex pavements is significant for traffic safety and the structural integrity highway bridges. This paper proposed an improved HRNet-OCR, named as segmentation network (EJSNet), automated pixel-level asphalt pavement. Different from high-resolution (HRNet), EJSNet modifies residual structure first stage by conducting a Conv. + BN ReLU (convolution batch normalization rectified linear unit) operation each shortcut connection, which can avoid...
Pixel-level detection of sealed cracks on pavements is great significance for pavement maintenance. The Multi-fusion U-net network based proposed to detect cracks. multi-fusion module, dual attention mechanism, and Atrous Spatial Pyramid Pooling (ASPP) are designed efficiently capture the details increase receptive field. Trained with a dataset 2463 crack images, demonstrated outperform DANet. experimental results indicate that F-measure IOU 200 testing images 84.36% 0.7295 respectively....