Publications (12)
Investigation of the Assessment of Infant Vocalizations by Laypersons
Franz Anders, Mario Hlawitschka, Mirco Fuchs
The goal of this investigation was the assessment of acoustic infant vocalizations by laypersons. More specifically, the goal was to identify (1) the set of most salient classes fo…
SoccerNet 2025 Challenges Results
Silvio Giancola, Anthony Cioppa, Marc Gutiérrez-Pérez +115
The SoccerNet 2025 Challenges mark the fifth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision research in football video understandi…
Using deep neural networks to detect non-analytically defined expert event labels in canoe sprint force sensor signals
Sarah Rockstroh, Patrick Frenzel, Daniel Matthes +3
Assessing an athlete's performance in canoe sprint is often established by measuring a variety of kinematic parameters during training sessions. Many of these parameters are relate…
Regression or Classification? Reflection on BP prediction from PPG data using Deep Neural Networks in the scope of practical applications
Fabian Schrumpf, Paul Rudi Serdack, Mirco Fuchs
Photoplethysmographic (PPG) signals offer diagnostic potential beyond heart rate analysis or blood oxygen level monitoring. In the recent past, research focused extensively on non-…
Compensating class imbalance for acoustic chimpanzee detection with convolutional recurrent neural networks
Franz Anders, Ammie K. Kalan, Hjalmar S. Kühl +1
Automatic detection systems are important in passive acoustic monitoring (PAM) systems, as these record large amounts of audio data which are infeasible for humans to evaluate manu…
Similarity based hierarchical clustering of physiological parameters for the identification of health states - a feasibility study
Fabian Schrumpf, Gerold Bausch, Matthias Sturm +1
This paper introduces a new unsupervised method for the clustering of physiological data into health states based on their similarity. We propose an iterative hierarchical clusteri…