Crack Monitoring from Motion (CMfM): Crack detection and measurement using cameras with non-fixed positions

Belloni, V., Sjölander, A., Ravanelli, R., Crespi, M., and Nascetti, A.: Crack Monitoring from Motion (CMfM): Crack detection and measurement using cameras with non-fixed positions, Automation in Construction, 156, doi.org/10.1016/j.autcon.2023.105072, 2023 

Code: github.com/Geod-Geom/CMfM

Towards Automated Inspections of Tunnels: A Review of Optical Inspections and Autonomous Assessment of Concrete Tunnel Linings 

Sjölander, A., Belloni, V., Ansell, A., and Nordström, E.: Towards Automated Inspections of Tunnels: A Review of Optical Inspections and Autonomous Assessment of Concrete Tunnel Linings, Sensors, 23(6), 3189, doi.org/10.3390/s23063189, 2023 

Experimental dataset to assess the structural performance of cracked reinforced concrete using Digital Image Correlation techniques with fixed and moving cameras

Sjölander, A., Belloni, V., Peterson, V., and Ledin, J.: Experimental dataset to assess the structural performance of cracked reinforced concrete using Digital Image Correlation techniques with fixed and moving cameras, Data in Brief, 51, doi.org/10.1016/j.dib.2023.109703, 2023 

Dataset: data.mendeley.com/datasets/z3yc9z84tk/3

TACK Project: Tunnel and Bridge Automatic Crack Monitoring Using Deep Learning and Photogrammetry

Belloni, V., Sjölander, A., Ravanelli, R., Crespi, M., and Nascetti, A.: TACK PROJECT: TUNNEL AND BRIDGE AUTOMATIC CRACK MONITORING USING DEEP LEARNING AND PHOTOGRAMMETRY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B4-2020, 741–745, doi.org/10.5194/isprs-archives-XLIII-B4-2020-741-2020, 2020