Automatic landslide detection with satellites and deep-learning
Developing a deep-learning model to automatically detect landslides from satellite images – supporting faster disaster response and safer land-use planning in a changing climate
Developing a deep-learning model to automatically detect landslides from satellite images – supporting faster disaster response and safer land-use planning in a changing climate
The project aims at generating and curating a high-quality dataset for air handling unit operation with emulated faults to develop fault detection and diagnosis solutions.
The FUMO project aims to find solutions for a sustainable and growing transport system in arctic urban and industrial conditions.
We will find the best solutions to extend the service life of existing concrete structures.
Sustainable and inclusive hybrid workplaces – anywhere and anytime?
Envelope mAterial System with low Impact for Zero Energy Renovation and construction
This preliminary project aimed to identify the new challenges faced by Ørland Municipality and Ørland Air Base as a result of a changing world, the new strategic significance of the Trøndelag region, and the associated shift in the threat landscape.
CLIMAREST is an EU-funded research project consisting of 18 partners from along the length of the European coastline. The project belongs to the EU Mission Restore our Ocean and Waters, and is a member of the Lighthouse for the Arctic and Atlantic...
Machine Sensible Infrastructure under Nordic Conditions