Nettsider med emneord «Machine Learning» - Side 5

Publisert 31. jan. 2019 09:54

Christos Dimitrakakis talks about the challenge of identity protection.

Publisert 8. nov. 2018 11:09
Publisert 18. okt. 2018 15:52
Publisert 24. sep. 2018 10:40
Publisert 23. sep. 2018 08:44

The SANT project will be presented at the Cutting Edge Festival.

Publisert 5. juni 2018 14:15
Publisert 5. juni 2018 14:11
Publisert 6. nov. 2017 11:32
Publisert 4. okt. 2017 14:53
Publisert 28. sep. 2017 21:05
Publisert 12. juni 2017 23:12

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.

Publisert 2. feb. 2017 10:58

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.

Publisert 21. des. 2016 15:29
Publisert 9. des. 2016 10:00
Publisert 8. nov. 2016 13:15

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.

Publisert 12. okt. 2016 09:51
Publisert 20. juni 2016 12:10

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.