A cascaded pavement layer thickness identification method based on deep learning recognition and electromagnetic signal interface tracking

Key Points

• Thickness identification achieved with deep learning recognition, enhancing the assessment of pavement layers.
• The model demonstrated a 95% accuracy in identifying thickness levels in various conditions.
• Cascaded approaches employing electromagnetic signal tracking were utilized to analyze pavement layers.
• The findings suggest improved methods for pavement evaluation, highlighting the need for advanced tracking techniques.