10 citations · 12 across the 5 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
eess.SP2023★ 2 cited
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse +3
As machine learning becomes increasingly prevalent in critical fields such as healthcare, ensuring the safety and reliability of machine learning systems becomes paramount. A key c…
eess.SP2023★ 10 cited
L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging
Huy Phan, Kristian P. Lorenzen, Elisabeth Heremans +7
Human sleep is cyclical with a period of approximately 90 minutes, implying long temporal dependency in the sleep data. Yet, exploring this long-term dependency when developing sle…