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.
May 12, 2022
Prof. Pierre Baldi visited Visual Intelligence in Tromsø, February 16-17, 2023. The two days were filled with fruitful meetings on potential scientific collaboration between UCI and Visual Intelligence.
Machine learning phd students from Visual Intelligence present at UiT The Arctic University of Norway's open day 2023, for recruitment of new students.
Pitch day at UiT for external master’s projects in computer science and machine learning
We approach the representation learning task by tackling the hubness problem.
We propose DeepMVC – a unified framework which includes many recent methods as instances.
By authors:
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer.
Published in:
CVPR 2023
on
March 6, 2023
By authors:
Daniel J. Trosten*, Rwiddhi Chakraborty*, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael Kampffmeyer (* indicates equal contribution)
Published in:
CVPR 2023
on
March 6, 2023
By authors:
Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Eivindson Løkse, Gusatu Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, and Robert Jenssen
Published in:
NAIS 2022 Communications in Computer and Information Science, vol 1650. Springer
on
February 2, 2023
By authors:
Changkyu Choi, Michael Kampffmeyer, Nils Olav Handegard, Arnt-Børre Salberg and Robert Jenssen
Published in:
IEEE Journal of Oceanic Engineering
on
February 1, 2023
By authors:
Debanshu Ratha, Andrea Marinoni and Torbjørn Eltoft
Published in:
IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1-16, 2023
on
December 23, 2022
By authors:
Suaiba Amina Salahuddin, Stine Hansen, Srishti Gautam, Michael Kampffmeyer, Robert Jenssen
Published in:
CEUR Workshop Proceedings 2022, Volum 3271.
on
November 13, 2022
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.
