We research the next generation of deep learning methodology for visual data and produce solutions for our consortium partners across innovation areas in medicine and health, marine science, energy, and earth observation.
June 18, 2026
Visual Intelligence gathered experts from Norwegian politics, research council, industry, the public sector, and academia to discuss the value of Norwegian AI competence and Norwegian-developed models.
Visual Intelligence researchers are attending two AI-oriented events at Arendalsuka 2026: Norway's largest annual political festival.
How can AI help detect diseases within our body? How can it monitor the Arctic climate? And how does AI even learn how to do these things in the first place? We bring together AI researchers from UiT to share the latest research – explained in simple terms.
Research shows how AI models can help, potentially making environmental monitoring faster and cheaper.
We propose the FC-DLIF model, which offers a non-invasive alternative that is flexible to temporal shifts and different scan durations
By authors:
Zhiyuan Wu, Changkyu Choi, Shujian Yu, Robert Jenssen, Ali Ramezani-Kebrya
Published in:
Transactions on Machine Learning Research (June/2026)
on
August 6, 2026
By authors:
Sigurd Almli Hanssen, Vilde Gjærum, Sara Björk, Elisabeth Wetzer, Arnt-Børre Salberg, Sébastien Lefèvre, Kristoffer Knutsen Wickstrøm
Published in:
Pending accept in renowned journal
on
August 1, 2026
By authors:
Juan Esteban Suarez Cardona, Holger Boche, Gitta Astrid Hildegard Kutyniok
Published in:
BIT Numerical Mathematics, 66:40, 2026
on
June 16, 2026
By authors:
Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen, Robert Jenssen, Michael Kampffmeyer
Published in:
MICCAI 2026
on
June 13, 2026
By authors:
Philipp Scholl, Aras Bacho, Holger Boche, Gitta Astrid Hildegard Kutyniok
Published in:
Mach Learn 115, 139 (2026)
on
May 29, 2026
By authors:
Zoé Lemoine, Puneet Sharma, Kit M. Kovacs, Christian Lydersen, Marie-Anne Blanchet
Published in:
Scientific Data
on
May 20, 2026
Visual Intelligence address the research challenges of deep learning and computer vision that limit our user partners in utilizing their complex visual data in their applications.
Read more
We contribute to reliable use of AI to detect heart disease, monitor the environment and potential natural disasters as well as detecting natural resources. Read more about our work in the different innovation areas.
Read moreVisual Intelligence is a consortium headed by UiT The Arctic University of Norway with research partners at the University of Oslo and the Norwegian Computing Center. Together with our consortium of high-profile user partners, we create cutting-edge solutions that will be implemented in the applications of the user partners.
