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.
Some of the recent talks from Visual Intelligence is now available for streaming on youtube. Recently we made available the opening lectures, VI seminars, and our workshop on limited training data. We continuously post our recorded webinars on the channel, so check it out.
Northern Lights Deep Learning Workshop 2021 is over and we are very happy with how it turned out! We want to thank all the contributors and the researchers from around the world that presented their work. We look forward to host NLDL also in 2022, but then physically in Tromsø!
The official opening of SFI Visual Intelligence was successfully arranged as a digital event today. We are now ready to commence our research and innovation to tackle some of the large challenges in deep learning and AI, along with our partners.
We collaborate with the Institute of Marine Research (IMR) to develop models and applications to detect and classify fish from echosounders.
Andrew Gilbert from GE Healthcare will in this seminar present work on generating synthetic labeled data from anatomical models with examples from Echocardiography Segmentation.
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 more
Visual 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.