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.
December 5, 2024
Andrew McDonald, a PhD student from University of Cambridge and the British Antarctic Survey, presented his work on sea ice forecasting with diffusion models, as well as the downstream applications of those forecasts, at Visual Intelligence in Tromsø.
Deep learning researchers from 27 different countries congregated at the 8th edition of the NLDL conference. - I have seen several interesting posters and talks that have opened my mind about different paths to explore in my own research, says NLDL 2025 attendee Tiago Ramos.
Annual Visual Intelligence workshop to strengthened technology transfer, as well as knowledge transfer within the Visual intelligence consortium.
We provide a theoretical understanding on the generalization error of momentum-based accelerated variants of stochastic gradient descent.
We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.
By authors:
Chakraborty, Rwiddhi; Wang, Yinong; Gao, Jialu; Zheng, Runkai; Zhang, Cheng; De la Torre, Fernando
Published in:
Advances in Neural Information Processing Systems
on
September 26, 2024
By authors:
Tran, Duy Khoi; Nguyen, van Nhan; Roverso, Davide; Jenssen, Robert; Kampffmeyer, Michael Christian.
Published in:
Expert Systems with Applications, Volume 250 , 2024, 123773
on
September 15, 2024
By authors:
Zheng, Kaizhong; Yu, Shujian; Li, Baojuan; Jenssen, Robert; Chen, Badong.
Published in:
IEEE Transactions on Neural Networks and Learning Systems
on
September 13, 2024
By authors:
Zheng, Kaizhong; Yu, Shujian; Li Baojuan; Jenssen, Robert; Chen, Badong
Published in:
Applied Soft Computing, Volume 163 , 111855
on
September 1, 2024
By authors:
Marius Aasan, Odd Kolbjørnsen, Anne Schistad Solberg, Adín Ramirez Rivera
Published in:
ECCV (MELEX) 2024 Workshop Proceedings
on
August 28, 2024
By authors:
Breznik, Eva; Wetzer, Elisabeth; Lindblad, Joakim; Sladoje, Nataša
Published in:
Scientific Reports
on
August 13, 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.
