Cyvl
The CYVL project involved the annotation of up to 50,000 images aimed at identifying both the materials used in road construction (e.g., asphalt, concrete, gravel) and various road surface defects such as potholes, cracks, repairs, and worn-out road markings. The scope required detailed classification and segmentation to support AI models used in automated road condition assessments and maintenance planning. Accuracy and consistency were critical, as the data contributed to infrastructure monitoring systems and smart city applications.