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:
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
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
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
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
By authors:
Jozwicki, D., Sharma, P., Huyghebaert, D., and Mann, I.
Published in:
Ann. Geophys., 42, 431–453,
on
November 11, 2024
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 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.
