Visual Intelligence unites three of the most experienced and best research institutions in deep learning and machine learning for visual data in Norway. The research partners have a history of long-time collaboration, joint positions and joint projects, and have complementary strengths.
UiT is the host organization of Visual Intelligence and within machine learning, UiT is the leading national research environment. The Machine Learning research group at UiT (machine-learning.uit.no) has long pushed the frontier of machine learning research within health technology, computer vision and industry-related research, to name a few. Visual Intelligence is for UiT a major component our interdepartmental study program in AI.UiT The Arctic University of Norway UiT Machine Learning Group
UiO and their digital and signal image analysis (DSB) group is leading in image analysis. For UiO machine learning is an important part of the strategy of the Department of Informatics, and the Faculty for Natural Science. Visual Intelligence will also be a natural part of a new section for Machine Learning at Department of Informatics, and a new centre for Data Science and Computational Science at UiO.UiO: University of Oslo
NR is a private, independent, non-profit foundation established in 1952. NR carries out contract research and development projects in the areas of information and communication technology and applied statistical modeling. For NR projects involving visual data have for decades been important, and the volume has increased significantly over the last years, especially by the use of deep learning techniques. NR’s ambitious aim is to be the European leader of applied deep learning research and innovation. Visual Intelligence is crucial to fulfil these ambitions.Norwegian Computing Centre, NR
At Visual Intelligence we enable our consortium partners to utilize the full potential of their complex visual data and contribute to development of new and improved products and services.
Cancer Registry of Norway are responsible for cancer screening in Norway and are currently investigating AI in mammographic screening. Demand is expected to rise for population-based screenings for more cancer forms. For this to be feasible, reliable automatic or semi-automatic solutions are needed. This will also enable use of more data and systematic analyses for changes over time, to help in the fight against cancer.Cancer Registry of Norway
Equinor has a major goal of becoming more data-driven and maximizing the value of the vast amount of data available; especially on the Norwegian Continental Shelf. A part of this includes challenges related to analysis of the digital subsurface, e.g. in the form of seismic and borehole imagery, which is important for oil and gas exploration. Automated analysis of these data can lead to large savings in time and resources and more efficient and precise exploration.Equinor
Field is a European leader in digital reality services. By combining software, sensors, and autonomous technologies, Field put data to work to boost efficiency and reliability within the infrastructure, construction, environment, and public sectors. With our 20+ unmanned aircraft systems, a fleet of 80 specialized work vehicles and 5 airplanes, we capture geo-referenced data, process it, and present it through our software applications. In 2020 we acquired 1.200.000 photos and 61.000 km2 Lidar data. Driven by the need to build and maintain the world’s infrastructure in a sustainable way, we empower modern society by transforming data into insights and living digital twins. Field has 300 employees in 13 locations with headquarter in Oslo and R&D departments in several locations.Field
GE Vingmed Ultrasound is a world leader in cardiovascular ultrasound. They want to develop innovative products through increasingly more intelligent cardiac ultrasound scanners capable of assisting the user to increased productivity and accelerated decision making. This can give both improved diagnostic accuracy, and improved productivity of the cardiac radiologists by automating repetitive tasks.GE Vingmed Ultrasound
IMR has a mission to be a leader in providing knowledge to ensure sustainable management of resources in our marine ecosystems. Their monitoring and research activities are to a large extent data driven, and efficient data analysis and processing pipelines are important to achieve their mission. They collect vast amounts of complex marine observation data containing valuable information needed to ensure sustainable fisheries and monitor the ecosystems. Manual analysis of these is a bottleneck, and automated solutions are needed for the next generation marine big data services.Institute of Marine Research, IMR
KSAT is Norway’s main satellite data provider specializing in delivery of operational near real-time services to an international market. A main interest of KSAT is improvement of the existing maritime surveillance services for vessel detection and oil spill monitoring. The center will enable KSAT to develop more efficient analysis and fast delivery of such products to improve service quality and decrease production time.Kongsberg Satellite Services
Helse Nord IKT works in tandem with UNN with special expertise on the hospital workflow for medical image analysis and interpretation, ICT infrastructure, and large-scale deployment of clinical solutions. Results from the center will enable Helse Nord IKT to develop new clinical solutions and services, for the benefit of individual hospitals and the entire health region in North Norway.Northern Norway Regional Health Authority ICT (Helse Nord IKT)
UNN’s main objective is to provide diagnosis and treatment at an international high level for the population in Northern Norway. UNN wants to explore deep learning technology for the detection of locally spread lymph node metastasis in rectal cancer and implications for therapeutic strategy. New AI tools for diagnostic accuracy and possible aid for radiologists and clinicians for colorectal cancer patients with metastasis to the liver is of great interest for UNN, as well as improved MRI diagnosis of prostate cancer.University Hospital of North Norway, UNN