Application of Segment Anything Model for Civil Infrastructure Defect Assessment

Understand

This research assesses the performance of two deep learning models, SAM and U-Net, for detecting cracks in concrete structures.

• The results indicate that each model has its own strengths and limitations for detecting different types of cracks.
• Using the SAM's unique crack detection approach, the image is divided into various parts that identify the location of the crack, making it more effective at detecting longitudinal cracks.
• On the other hand, the U-Net model can identify positive label pixels to accurately detect the size and location of spalling cracks.