From the 1 of 5 linked papers with an AI index.
5 papers
AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts
Niklas Grieger, Jannik Raskob, Siamak Mehrkanoon +1
AnySleep is a deep learning system that automatically stages sleep using EEG or EOG data at flexible time resolutions, and it works well across many clinical sites and electrode se…
From Sleep Staging to Spindle Detection: A Case Study on End-to-End Automated Sleep Analysis
Niklas Grieger, Siamak Mehrkanoon, Philipp Ritter +1
Automation of sleep analysis, including both macrostructural (sleep stages) and microstructural (e.g., sleep spindles) elements, promises to enable large-scale sleep studies and to…
Data-Efficient Sleep Staging with Synthetic Time Series Pretraining
Niklas Grieger, Siamak Mehrkanoon, Stephan Bialonski
Analyzing electroencephalographic (EEG) time series can be challenging, especially with deep neural networks, due to the large variability among human subjects and often small data…
AIxcellent Vibes at GermEval 2025 Shared Task on Candy Speech Detection: Improving Model Performance by Span-Level Training
Christian Rene Thelen, Patrick Gustav Blaneck, Tobias Bornheim +2
Positive, supportive online communication in social media (candy speech) has the potential to foster civility, yet automated detection of such language remains underexplored, limit…
Detecting Sexism in German Online Newspaper Comments with Open-Source Text Embeddings (Team GDA, GermEval2024 Shared Task 1: GerMS-Detect, Subtasks 1 and 2, Closed Track)
Florian Bremm, Patrick Gustav Blaneck, Tobias Bornheim +2
Sexism in online media comments is a pervasive challenge that often manifests subtly, complicating moderation efforts as interpretations of what constitutes sexism can vary among i…