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.
October 10, 2024
Our summer students have worked on projects related to fatigue and stress recognition with machine learning as their first research experience. Their results were presented at Georg Sverdrups hus at University of Oslo on October 16th 2024.
PhD candidate Rwiddhi Chakraborty recently gave an invited research talk titled "Perspectives on Multimodal Reasoning" at the Pioneer Centre for AI at University of Copenhagen.
NLDL is the northernmost annual science conference within artificial intelligence and deep learning. The conference gathers researchers from across the globe to exchange ideas, encourage collaborations and present cutting-edge research in the cool arctic environment of Tromsø, Norway.
We propose ConBias, a bias diagnosis and debiasing pipeline for visual datasets.
MaSSL is a novel approach to self-supervised learning that enhances training stability and efficiency.
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.
