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Found 3 papers, 1 papers with code
Real-Time Asphalt Pavement Layer Thickness Prediction Using Ground-Penetrating Radar Based on a Modified Extended Common Mid-Point (XCMP) Approach
This study investigates the affecting factors and develops a modified XCMP method to allow automatic thickness prediction of in-service asphalt pavement with non-uniform dielectric properties through depth.
Polar-Doc: One-Stage Document Dewarping with Multi-Scope Constraints under Polar Representation
While Cartesian coordinates are typically leveraged by state-of-the-art approaches to learn a group of deformation control points, such representation is not efficient for dewarping model to learn the deformation information.
Pavementscapes: a large-scale hierarchical image dataset for asphalt pavement damage segmentation
However, few current public datasets limit the potential exploration of deep learning in the application of pavement damage segmentation.
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