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 #70: Representation Learning of Visual Features Through Self-Supervision

February 27, 2025

Latest news

forskning.no: Derfor fungerer KI dårligere på kvinner

March 8, 2025

Det hender at kunstig intelligens behandler menn og kvinner ulikt. Hvordan skjer dette? KI-forsker Elisabeth Wetzer forklarer hva som ligger bak skjevhetene i teknologien (Popular science story in forskning.no and sciencenorway.no)

When:
March 13, 2025
,
13:00
March 13, 2025
,
14:00
@
Online

Professor Orcun Goksel, Dept. of Information Technology, Uppsala University, Sweden

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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.

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Modular Superpixel Tokenization in Vision Transformers

March 6, 2025

ViTs partition images into square patches to extract tokenized features. But is this necessarily an optimal way of partitioning images?

Recent publications

Motion compansated interpolation in echocardiography: A Lie-advection based approach

By authors:

H. N. Mirar, S. R. Snare and A. H. S. Solberg

Published in:

IEEE Transactions on Biomedical Engineering, vol. 72, no. 1, pp. 123-136, Jan. 2025

on

January 16, 2025

From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation

By authors:

Wickstrom, Kristoffer; Höhne, Marina; Hedström, Anna.

Published in:

European Conference on Computer Vision (ECCV) 2024 Workshop: Explainable Computer Vision: Where are We and Where are We Going?, 2024.

on

December 7, 2024

Deep learning-based postoperative glioblastoma segmentation and extent of resection evaluation: Development, external validation, and model comparison

By authors:

Santiago Cepeda, Roberto Romero, Lidia Luque, Daniel García-Pérez, Guillermo Blasco, Luigi Tommaso Luppino, Samuel Kuttner, Olga Esteban-Sinovas, Ignacio Arrese, Ole Solheim, Live Eikenes, Anna Karlberg, Ángel Pérez-Núñez, Olivier Zanier, Carlo Serra, Victor E Staartjes, Andrea Bianconi, Luca Francesco Rossi, Diego Garbossa, Trinidad Escudero, Roberto Hornero, Rosario Sarabia

Published in:

Neuro-Oncology Advances, Volume 6, Issue 1, January-December 2024, vdae199

on

November 16, 2024

Polar mesospheric summer echo (PMSE) multilayer properties during the solar maximum and solar minimum

By authors:

Jozwicki, D., Sharma, P., Huyghebaert, D., and Mann, I.

Published in:

Ann. Geophys., 42, 431–453,

on

November 11, 2024

Better, Not Just More: Data-centric machine learning for Earth observation

By authors:

Roscher, Ribana; Russwurm, Marc; Gevaert, Caroline; Kampffmeyer, Michael Christian; Santos, Jefersson A. Dos; Vakalopoulou, Maria; Hansch, Ronny; Hansen, Stine; Nogueira, Keiller; Prexl, Jonathan; Tuia, Devis

Published in:

EEE Geoscience and Remote Sensing Magazine 2024 s. 1-22

on

October 31, 2024

Visual Data Diagnosis and Debiasing with Concept Graphs

By authors:

Chakraborty, Rwiddhi; Wang, Yinong; Gao, Jialu; Zheng, Runkai; Zhang, Cheng; De la Torre, Fernando

Published in:

Advances in Neural Information Processing Systems

on

September 26, 2024

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