Exploiting context, dependencies and prior knowledge in deep learning
Utilizing the best of classical- and machine learning models to unlock the potential in complex image data.
The strength of machine learning methods is the ability to learn from data rather than using predefined models. For complex data there is however a need to integrate the best of these two worlds to enable integration of physical or geometrical models, dependencies, and prior knowledge, as well as the exploitation of multiple complex image modalities simultaneously.
Current deep learning systems for image analysis depend on individual pixel information, capturing dependencies solely via the convolution neighborhood. This means that the ability to incorporate context and prior knowledge, e.g. about topology or boundaries, is limited. The ability to conform to physical models, and principles governing the image data generation and its properties is also limited, including modelling of temporal dependencies and processes.
Hence, in order to make deep learning based computer vision systems ubiquitous and applicable also for complex, sparsely labelled image data, there is a need for visual intelligence that can easily be adapted to new, non-standard data sources with few labelled training samples.
Official opening of Visual Intelligence research centre!
January 19, 2021
January 14, 2021 the official opening of SFI Visual Intelligence will be organized at the UiT - The Arctic University of Norway. Anne Husebekk, the rector of UiT will be giving a speech at the opening ceremony.
NLDL 2021 will be a digital conference hosted by the UiT Machine Learning Group and Visual Intelligence January 18-20. The program includes a Mini Deep Learning School the 18th and is followed by a tight program the rest of the week.
Visual Intelligence will be one of the new SFIs funded by the Research Council of Norway. The center will run over a period of eight years and will form a collaboration between businesses and research institutions in Norway.
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.