Webpages tagged with «Machine Learning»
An important priority for LTG in recent years has been to create NLP resources for the Norwegian language, both in terms of modeling and datasets. This page provides an overview of our existing and ongoing projects to support Norwegian NLP.
In joint work, SANT and NLPL/EOSC-Nordic have trained and released the first large-scale transformer-based language model for Norwegian: NorBERT!
The SANT project develops resources for Sentiment Analysis for Norwegian Text. While coordinated by the Language Technology Group (LTG) at IFI/UiO, collaborating partners include NRK, Schibsted and Aller Media.
Obstructive sleep apnea (OSA) is a common but severely under-diagnosed sleep disorder that affects the natural breathing cycle during sleep with the periods of reduced respiration or no airflow at all. It is our long-term goal to increase the percentage of diagnosed OSA cases, reduce the time to diagnosis, and support long term monitoring of patients with user friendly and cost-efficient tools for sleep analysis at home. Core elements are mobile computing platforms (e.g., smartphones), consumer electronics sensors, and machine learning for OSA detection.
Two new papers from SANT were presented at the NoDaLiDa conference.
Signal processing, image analysis, and machine learning for applications in medical imaging, sonar, seismics, and remote sensing.
In this ongoing cross-disciplinary collaboration, researchers in Language Technology (LT) and Political Science (PS) are applying supervised and unsupervised machine learning methods to data from the Norwegian parliament in order to gather knowledge spanning across different dimensions.
Cardiac related disease is the number one cause of death in the Western world, including Norway. Echocardiography is the most important imaging tool for the cardiologist to assess cardiac function. An echo examination of the heart is real time, cost effective and can be performed without discomfort to the patient and without harmful radiation. These are great advantages compared to other medical imaging modalities.
The SANT project will be presented at the Cutting Edge Festival.
