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.
April 9, 2026
Visual Intelligence hosted over 45 international AI researchers for the DL2026 workshop at UiT The Arctic University of Norway.
Visual Intelligence will be well represented at MICCAI 2026, one of the leading AI conferences on medical imaging and computer assisted intervention, with two accepted research papers.
New study shows how deep learning can achieve human-level performance in estimating uncertainty when classifying foraminifera.
We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.
By authors:
Zhiyuan Wu,Changkyu Choi,Shujian Yu,Robert Jenssen,Ali Ramezani-Kebrya
Published in:
Transactions on Machine Learning Research (June/2026)
on
August 6, 2026
By authors:
Juan Esteban Suarez Cardona,Holger Boche,Gitta Astrid Hildegard Kutyniok
Published in:
BIT Numerical Mathematics, 66:40, 2026
on
June 16, 2026
By authors:
Scholl, Philipp,Bacho, Aras,Boche, Holger,Gitta Astrid Hildegard Kutyniok
Published in:
Mach Learn 115, 139 (2026)
on
May 29, 2026
By authors:
Zoé Lemoine,Puneet Sharma,Kit M. Kovacs,Christian Lydersen,Marie-Anne Blanchet
Published in:
Scientific Data
on
May 20, 2026
By authors:
Yang Bai,George Eskandar,Ziyuan Liu,Gitta Kutyniok
Published in:
ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, 2026, pp. 13242-13246
on
May 3, 2026
By authors:
Anna Emilie Jennow Wedenborg, Kristoffer Wickstrøm, Lars Kai Hansen, Morten Mørup, Teresa Dorszewski
Published in:
Proceedings of the 7th Northern Lights Deep Learning Conference (NLDL), PMLR 307:448-468, 2026.
on
May 1, 2026
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.
