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 5, 2025
Visual Intelligence will be well represented at MICCAI 2025—one of the leading AI conferences on medical imaging and computer assisted intervention—with three recently accepted research papers.
More than 50 attendees from the Norwegian AI research community gathered in Tromsø, Norway for two days of insightful presentations, interactive technical sessions, and scientific and social interactions.
Vi spør; Hva bør vi gjøre for å styrke forskningsdrevet innovasjon innen KI i Norge? Hvilke muligheter ligger i denne styrkingen? Hva er utfordringene, og hva må vi gjøres for å løse de? KI-senteret SFI Visual Intelligence ved UiT Norges arktiske universitet inviterer til en samtale mellom akademia, næringsliv og politikere for å diskutere disse spørsmålene.
We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.
ViTs partition images into square patches to extract tokenized features. But is this necessarily an optimal way of partitioning images?
By authors:
Changkyu Choi, Arangan Subramaniam, Nils Olav Handegard, Ali Ramezani-Kebrya and Robert Jenssen
Published in:
Proceedings of the Symposium of the Norwegian AI Society 2025, CEUR Workshop Proceedings ( ISSN 1613-0073)
on
June 17, 2025
By authors:
Marius Aasan, Adín Ramírez Rivera
Published in:
Proceedings of the Symposium of the Norwegian AI Society 2025, CEUR Workshop Proceedings ( ISSN 1613-0073)
on
June 17, 2025
By authors:
Suaiba A. Salahuddin, Elisabeth Wetzer, Kristoffer Wickstrøm, Solveig Thrun, Michael Kampffmeyer and Robert Jenssen
Published in:
Lecture Notes in Computer Science (LNCS) 2025 ;Volum 15726.
on
June 16, 2025
By authors:
Hyeongji Kim, Changkyu Choi, Michael Christian Kampffmeyer, Terje Berge, Pekka Parviainen, Ketil Malde
Published in:
Lecture Notes in Computer Science (LNCS) 2025
on
May 12, 2025
By authors:
Zhiyuan Wu, Changkyu Choi, Volkan Cevher, Ali Ramezani-Kebrya
Published in:
International Conference on Learning Representations 2025
on
April 29, 2025
By authors:
Nikita Shvetsov, Anders Sildnes, Masoud Tafavvoghi, Lill-Tove Rasmussen Busund, Stig Manfred Dalen, Kajsa Møllersen, Lars Ailo Bongo, Thomas K. Kilvaer,
Published in:
Journal of Pathology Informatics
on
March 12, 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.
