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.
October 23, 2025
Samuel Kuttner and Elin Kile presented research on PET and artificial intelligence at evening seminar on early detection of prostate cancer organized by the Norwegian Prostate Cancer Assocation.
Centre Director Robert Jenssen represented Visual Intelligence at Svarte Natta 2025 – North Norway's journalist and media conference organized by the Norwegian Union of Journalists.
Presented by Håkon Nese, Data Scientist at Aker BP. This seminar is open for members of the consortium. If you want to participate as a guest, please sign up.
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:
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:
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
By authors:
Durgesh Kumar Singh, Qing Cao, Sarina Thomas, Ahcène Boubekki, Robert Jenssen, Michael Kampffmeyer
Published in:
Simplifying Medical Ultrasound, ASMUS 2025 Workshop, MICCAI 2025
on
September 17, 2025
By authors:
Zijun Sun, Solveig Thrun and Michael Kampffmeyer
Published in:
MICCAI 2025
on
September 17, 2025
By authors:
Hyeongji Kim, Stine Hansen, Michael Kampffmeyer
Published in:
MICCAI 2025
on
September 17, 2025
By authors:
Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba A. Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Robert Jenssen, Maik Stille, Michael Kampffmeyer
Published in:
INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION (MICCAI) 2025
on
September 17, 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.
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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.
