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 #55 – Earth Observation Foundation Models and their Applications

April 11, 2024

Latest news

Visual Intelligence researchers featured in "Abels Tårn"

April 12, 2024

Visual Intelligence researchers featured in "Abels Tårn"Visual Intelligence researchers from UiT Machine Learning Group and the University Hospital of North Norway (UNN) were recently featured in the "Abels Tårn" spin-off show "Den store serien om KI".

Pascal Fua visits Visual Intelligence in Tromsø

April 9, 2024

While visiting Tromsø, Fua held two talks on the topics of "Deep Uncertainty" and "Deep 3D Surface Meshes" for students and researchers at UiT The Arctic University of Norway.

When:
May 30, 2024
,
0:00
May 30, 2024
,
16:00
@
Scandic Grand Hotell

Under Grafisk bransjeforening Nords 75-års-jubileumskonferanse vil førsteamanuensis Kristoffer Wickstrøm (UiT) holde et foredrag om "kunstig intelligens: utfordringer og muligheter for næringslivet".

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Interrogating Sea Ice Predictability With Gradients

March 22, 2024

The paper focuses on interrogating the effect of the IceNet's input feature with a gradient-based analysis.

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On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering

December 19, 2023

We propose DeepMVC – a unified framework which includes many recent methods as instances.

Recent publications

Interrogating Sea Ice Predictability With Gradients

By authors:

Joakimsen, H. L., Martinsen I., Luppino, L. T., McDonald, A., Hosking, S., and Jenssen, R.

Published in:

IEEE Geoscience and Remote Sensing Letters

on

February 14, 2024

Mixed Nash for Robust Federated Learning

By authors:

Xie, Wanyun; Pethick, Thomas; Ramezani-Kebrya, Ali; Cevher, Volkan

Published in:

Transactions on Machine Learning Research (02/2024)

on

February 4, 2024

On the Generalization of Stochastic Gradient Descent with Momentum

By authors:

Ali Ramezani-Kebrya, Kimon Antonakopoulos, Volkan Cevher, Ashish Khisti, Ben Liang

Published in:

Journal of Machine Learning Research 25 (2024) 1-56

on

January 1, 2024

A Contextually Supported Abnormality Detector for Maritime Trajectories

By authors:

Olesen, Kristoffer Vinther; Boubekki, Ahcene; Kampffmeyer, Michael Christian; Jenssen, Robert; Christensen, Anders Nymark; Hørlück, Sune; Clemmensen, Line H. A

Published in:

Journal of Marine Science and Engineering (JMSE) 2023 ;Volum 11.(11)

on

October 31, 2023

View it like a radiologist: Shifted windows for deep learning augmentation of CT images

By authors:

Østmo, Eirik Agnalt; Wickstrøm, Kristoffer; Radiya, Keyur; Kampffmeyer, Michael; Jenssen, Robert.

Published in:

2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP), Rome, Italy, 2023, pp. 1-6

on

October 23, 2023

On Measures of Uncertainty in Classification

By authors:

Chlaily, Saloua; Ratha, Debanshu; Lozou, Pigi; Marinoni, Andrea

Published in:

IEEE Transactions on Signal Processing 2023 ;Volum 71. s.3710-3725

on

October 12, 2023

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 logoNorwegian Computing Centre logoUniversity hospital of north norway logoHelse nord ikt logoInstitute of marine research logoKongsberg satellite services logoGE Healthcare logoEquinor logoCancer Registry of Norwat logo