Presented by Anders Waldeland, Senior Research Scientist at the Norwegian Computing Center
The Norwegian Computing Center has been working on automating the inspection and monitoring of railway infrastructure for the last 5 years in collaboration with Bane NOR. Together, NR and Bane NOR are developing a mobile and cost-efficient camera system that can be mounted on the front of maintenance trains to record video of the infrastructure.
We have been using deep learning–based computer vision on this data to detect faults, identify anomalies, and perform positioning for change detection. In this presentation, Anders Waldeland talks about this work and how we have been using various foundation models and self-supervised learning to advance automatic inspection.