A Norwegian centre for research-based innovation

Through long-term research in close collaboration between industry, public institutions and prominent research partners, we enable novel innovations, technology transfer, internationalization and researcher training.

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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.

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VI Seminar #79: Diffusion Model Meets XAI: Counterfactual Generation for Model Debugging

August 28, 2025

Latest news

uit.no: Hvordan håndtere skjevheter og beskytte personvernet i KI-alderen?

September 11, 2025

Det skal eksperter på kunstig intelligens, cybersikkerhet og juss fra UiT Norges arktiske universitet diskutere på Verdensteatret Kino den 17. september. Arrangementet er gratis og åpen for alle (Norwegian news article at uit.no)

When:
September 17, 2025
,
18:00
September 17, 2025
,
20:30
@
Verdensteatret Kino

Join us for a night at Verdensteatret for a free movie screening of "Coded Bias": an award-winning documentary which investigates the bias in AI algorithms after M.I.T. Media Lab researcher Joy Buolamwini uncovered flaws in facial recognition technology.The screening will be followed by a 40-minute panel discussion between AI, law and cybersecurity experts.

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AI matches human experts in classifying microscopic organisms

August 15, 2025

New study shows how deep learning can achieve human-level performance in estimating uncertainty when classifying foraminifera.

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Visual Data Diagnosis and Debiasing with Concept Graphs

March 6, 2025

We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.

Recent publications

SPoT: Subpixel Placement of Tokens in Vision Transformers

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

Low-Rank Adaptations for increased Generalization in Foundation Model features

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

WiseLVAM: A Novel Framework For Left Ventricle Automatic Measurements

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

VMRA-MaR: An Asymmetry-Aware Temporal Framework for Longitudinal Breast Cancer Risk Prediction

By authors:

Zijun Sun, Solveig Thrun and Michael Kampffmeyer

Published in:

MICCAI 2025

on

September 17, 2025

Tied Prototype Model for Few-Shot Medical Image Segmentation

By authors:

Hyeongji Kim, Stine Hansen, Michael Kampffmeyer

Published in:

MICCAI 2025

on

September 17, 2025

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction

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

Research challenges

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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Innovation areas

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.

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Our partners

Visual 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.

UiT The Arctic University of Norway logoUiO: University of Oslo logoUniversity hospital of north norway logoHelse nord ikt logoInstitute of marine research logoKongsberg satellite services logoGE Healthcare logoEquinor logoCancer Registry of Norwat logo