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 10, 2025
Senior Researcher Fredrik Dahl recently gave a talk about Norsk Regnesentral's work on developing AI algorithms for automatic analysis of image quality and cancer detection at Norsk Radiografforbund's mammography symposium in Oslo.
Han høster anerkjennelse for sitt forskningsarbeid innen utvikling av mer effektive KI-modeller (Norwegian news article in Nordlys).
Dr. Donghyun Ahn and Dr. Jeasurk Yang, Max Planck Institute for Security and Privacy
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.
