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 hosted over 45 international AI researchers for the DL2026 workshop at UiT The Arctic University of Norway.
Visual Intelligence will be well represented at MICCAI 2026, one of the leading AI conferences on medical imaging and computer assisted intervention, with two accepted research papers.
New study shows how deep learning can achieve human-level performance in estimating uncertainty when classifying foraminifera.
We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.
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:
Anna Emilie Jennow Wedenborg, Kristoffer Wickstrøm, Lars Kai Hansen, Morten Mørup, Teresa Dorszewski
Published in:
Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:448-468, 2026.
on
May 1, 2026
By authors:
Karim Galliamov,Syed M Ahsan Kazmi,Adil Mehmood Khan,Adín Ramírez Rivera
Published in:
International Conference on Learning Representations (ICLR), 2026
on
April 23, 2026
By authors:
Martine Hjelkrem-Tan, Marius Aasan, Rwiddhi Chakraborty, Gabriel Y. Arteaga, Changkyu Choi, Adín Ramirez Rivera
Published in:
CPVR 2026
on
March 31, 2026
By authors:
Christian Salomonsen, Luigi T. Luppino, Fredrik Aspheim, Kristoffer Wickstrøm, Elisabeth Wetzer, Michael Kampffmeyer, Rodrigo Berzaghi, Rune Sundset, Robert Jenssen & Samuel Kuttner
Published in:
EJNMMI Res 16, 65 (2026)
on
March 9, 2026
By authors:
Durgesh Kumar Singh, Ahcene Boubekki, Robert Jenssen, Michael Kampffmeyer
Published in:
Pattern Recognition, vol 171, Part A, Article: 112117
on
March 3, 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.
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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.
