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
Visual intelligence og norske forskningssentre innen kunstig intelligens er klare til å bidra til regjeringens ambisiøse milliardsatsning på KI for å utvikle trygg, pålitelig, og effektiv kunstig intelligens som vil gagne samfunnet, innovasjonen og utdanningen.
Maskinlæringsgruppa ved UiT skal i gang med å lage en permanent utstilling om kunstig intelligens. Målet er å rekruttere fremtidens forskere innen faget.
Afternoon program for young researchers and graduate students
Introducing the SuperCM technique to significantly improve classification results across various types of image data.
Training and test data from different clients pose a challenge.
By authors:
Xujie Zhang, Binbin Yang, Michael C. Kampffmeyer, Wenqing Zhang, Shiyue Zhang, Guansong Lu, Liang Lin, Hang Xu, Xiaodan Liang
Published in:
ICCV 2023
on
August 20, 2023
By authors:
Haoyuan Li, Haoye Dong, Hanchao Jia, Dong Huang, Michael C. Kampffmeyer, Liang Lin, Xiaodan Liang
Published in:
ICCV 2023
on
August 20, 2023
By authors:
Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer
Published in:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
on
June 4, 2023
By authors:
Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher
Published in:
Transactions on Machine Learning Research
on
June 1, 2023
By authors:
Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina MC Höhne
Published in:
Transactions on Machine Learning Research (06/2023)
on
June 1, 2023
By authors:
Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher
Published in:
International Conference on Learning Representations ICLR 2023
on
May 1, 2023
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.
Read more
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.
