福利姬

Develops edge competence in visual AI, visualization, graphics and human-centered tech with strong human-in-the-loop focus. Combines research excellence with national and international collaboration for societal impact.

We work at the intersection of computer graphics, AI-driven visualization, computer vision, and machine learning to address complex scientific challenges.

Projektet utvecklar nya metoder för storskaliga växthusgasflödesmätningar med drönare, för att noggrant kvantifiera flöden av metan, lustgas och koldioxid. Detta möjliggör bättre bedömningar och reglering av klimatkänsliga utsläpp från landskap.

CSPR is a platform for knowledge production to trigger and promote societal changes towards safe and just climate futures for all. Our goal is to create knowledge and methodological approaches that can support and advance climate actions.

We explore a visualization globe that combines interactive visualizations and artificial intelligence.

We develop and implement medical image analysis methods using deep learning. Our medical focus areas are cancer, orthopedics and body composition analysis using multiple image and data modalities.

We conduct internal and external production development with the goal of combining research data and visualization technology for improved science communication and use beyond research, with a focus on the public, schools and business.

CMIV conducts focused front-line research providing solutions to tomorrow鈥檚 clinical issues. The CMIV mission is to develop future methods and tools for image analysis and visualization for applications within health care and medical research.

Virtual Worlds explores the role of digital technologies in managing climate change and biodiversity loss. The program reviews how technology can improve environmental governance and include local knowledge for sustainable development.

Advanced CT creates amazing visualization of the beating heart. However, the complex interactions of blood flow are not fully reflected by these images. This project aims to extract blood flow data from CT images using image-based simulations.