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.
January 29, 2026
We happily welcome Keyne Oei and Boye Sjo as new PhD Research Fellows at SFI Visual Intelligence in Tromsø and Oslo respectively.
Congratulations to Børge Solli Andreassen, who successfully defended his PhD thesis at the University of Oslo on December 18th 2025.
Annual Visual Intelligence workshop to strengthen technology transfer and knowledge transfer within the centre consortium
Training and test data from different clients pose a challenge.
We provide a theoretical understanding on the generalization error of momentum-based accelerated variants of stochastic gradient descent.
By authors:
Nikita Shvetsov, Thomas Karsten Kilvær, Masoud Tafavvoghi, Anders Sildnes, Kajsa Møllersen, Lill-Tove Rasmussen Busund, Lars Ailo Bongo
Published in:
Computers in Biology and Medicine, Volume 199, 2025
on
December 1, 2025
By authors:
Martine Hjelkrem-Tan, Marius Aasan, Gabriel Y. Arteaga, and Adín Ramírez Rivera
Published in:
Workshop on Efficient Computing under Limited Resources: Visual Computing (ICCV 2025), Oct 19 – 23th, 2025, Honolulu, Hawai'i
on
October 19, 2025
By authors:
Thea Brüsch, Kristoffer Wickstrøm, Mikkel N. Schmidt, Robert Jenssen, Tommy Sonne Alstrøm
Published in:
Explainable Artificial Intelligence. xAI 2025. Communications in Computer and Information Science, vol 2579. Springer
on
October 14, 2025
By authors:
Teresa Dorszewski, Lenka Tětková, Robert Jenssen, Lars Kai Hansen, Kristoffer Knutsen Wickstrøm
Published in:
Communications in Computer and Information Science, vol 2576. Springer 2025
on
October 12, 2025
By authors:
Duy Khoi Tran, Van Nhan Nguyen, Kristoffer Wickstrøm, Michael Kampffmeyer
Published in:
International Journal of Electrical Power & Energy Systems, Volume 171, 2025, 110900, ISSN 0142-0615
on
October 1, 2025
By authors:
Vilde Schulerud Bøe, Andreas Kleppe, Sebastian Foersch, Daniel-Christoph Wagner, Lill-Tove Rasmussen Busund, Adín Ramírez Rivera
Published in:
MICCAI Workshop on Computational Pathology with Multimodal Data (COMPAYL), DAEJEON, South Korea, 2025
on
September 27, 2025
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.
