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Machine learning seminar: A machine learning mini-conference

October 17, 2018 @ 14:15 - 17:00

Are you curious about what deep learning-related projects are ongoing in Bergen? Want a taste of what you can do with deep learning? Interested in meeting like-minded people? Free coffee? Then you shouldn’t miss our next machine learning seminar, October 17th at Haukeland University Hospital! Five masters students and a PhD candidate working on projects related to the Mohn Medical Imaging and Visualization Center (https://mmiv.no) will give speed-presentations of their projects. 12 minutes + 3 minutes for questions. There will also be a short 10-minute presentation of the context of their work. After the presentations there will be time for socializing and discussions, and also a small exhibition of some ongoing work.

Even if you’re not working on problems related to medical data analysis, you’ll likely get something out of the seminar. As you know, machine learning techniques are highly transferable.

Please sign up here: https://mmiv.no/ml-seminar. Consider joining our mailing list: https://mmiv.no/ml-seminar


14.15–14.30: Machine learning in medical imaging. A super-quick glimpse into what’s possible.
Alexander S. Lundervold, assoc. prof at HVL and researcher at MMIV

14.30–14.45: Deep transfer learning. Can a network trained to do a task be reused for other tasks?
Satheshkumar Kaliyugarasan, MSc student at HVL

14.45–15:00: Brain connectivity, machine learning and irritable bowel syndrome
Peder Lillebostad, MSc student at UiB
Samaneh Mofrad, PhD candidate at HVL

15.00–15.15: Break

15.15–15:30: Combining robotics and deep learning – Real-time Human Action Recognition.
Sindre Eik de Lange, MSc student at HVL
Stian Heilund, MSc student at HVL

15.35–15.45: Predictions from clinical data. Who’s in need of more careful monitoring?
Andreas Hammerbeck, MSc student at HVL


October 17, 2018
14:15 - 17:00
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Library/Auditorium (H112/H113), Dept of Radiology, Haukeland University Hospital
Sentralblokken Haukeland
Bergen, Norway
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