Crack detection is essential for structural safety inspection but remains challenging due to noise, illumination variations, and complex backgrounds. In this paper, we propose CrackNet, a segmentation
Combined information about all vent and fracture locations. The second row contains additional information about the instruments used to collect the data presented in the column.
Accurate crack segmentation plays a crucial role in ensuring safety and mitigating disaster risks during road inspections and structural health monitoring. However, traditional image processing techni
This excel file contains the raw data related to the cycle tests performed on the self-sensing GFRP powder laminates for the paper "On the design of a piezoelectric self-sensing smart composite lamina