4 citations · 10 across the 21 of their papers we have counts for
25 papers
Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning
Simon Süwer, Julian Klemm, Elisa Acitelli +39
Federated learning enables collaborative training without sharing patient-level data, but most studies remain simulations. Based on five requirements derived from the literature, w…
Not All Nodes Are Created Equal: Homophily-Aware Stratification for Stable GNN Evaluation
Naga Venkata Sai Jitin Jami, Thomas Altstidl, Sebastian Hoefler +4
Graph neural networks are widely used for transductive node classification, with accuracy typically measured on randomly drawn train/validation/test splits. Reported accuracy has b…
Do Depressive Facial Patterns Transfer Across Cultures and Contexts? Evidence from a German RCT and E-DAIC
Misha Sadeghi, Robert Richer, Lydia Helene Rupp +7
Automated assessment of depression from facial dynamics holds promise for scalable mental health monitoring, yet cross-corpus generalization of learned biomarkers remains an open c…
How LLMs Build Fictional Worlds: Setting and Narrative Space in AI-Generated Creative Storytelling
Katrin Rohrbacher, Björn Nieth, Emmanuelle Salin +2
In this paper, we analyze how Large Language Models (LLMs) employ worldbuilding strategies, focusing on setting as one measurable dimension of storyworld construction. We compare 1…
You Only Flow Once: Calibrated and Real-Time Radar Pose Estimation with Multi-Hypothesis Normalizing Flows
Jonas Leo Mueller, Sebastian Hoefler, Dario Zanca +3
Sparse and noisy millimeter-wave radar point cloud observations often correspond to multiple plausible human poses, making deterministic pose estimation fundamentally ill-posed. Ye…
Learning Biomechanically Plausible Human Motion from Sparse Radar Point Clouds
Jonas Leo Mueller, Markus Gambietz, Alexander Weiss +2
Radar-based human pose estimation has focused on improving learning algorithms while representing the body as unconstrained keypoint coordinates. We address the underexplored dimen…
Multi-Channel Soil Moisture Measurement: High Accuracy and Low Crosstalk Through Optical-Semiconductor Based Differential Sensing
Thomas Maier, Charlotte Rohleder, Lukas Kamm +3
Soil moisture measurement plays a key role in irrigation and environmental management. Yet it remains unreliable due to heterogeneous soils, limited sensing volumes, temperature dr…
How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework
Björn Nieth, Marianna Gracheva, Michaela Mahlberg +2
While factual correctness and task-performance have been in focus of Large Language Model (LLM) research for a long time, the fundamental question of how human-like generated texts…
ContraLog: Log File Anomaly Detection with Contrastive Learning and Masked Language Modeling
Simon Dietz, Kai Klede, An Nguyen +1
Log files record computational events that reflect system state and behavior, making them a primary source of operational insights in modern computer systems. Automated anomaly det…
Stratify or Die: Rethinking Data Splits in Image Segmentation
Naga Venkata Sai Jitin Jami, Thomas Altstidl, Jonas Mueller +4
Random splitting of datasets in image segmentation often leads to unrepresentative test sets, resulting in biased evaluations and poor model generalization. While stratified sampli…
REVELIO -- Universal Multimodal Task Load Estimation for Cross-Domain Generalization
Maximilian P. Oppelt, Andreas Foltyn, Nadine R. Lang-Richter +1
Task load detection is essential for optimizing human performance across diverse applications, yet current models often lack generalizability beyond narrow experimental domains. Wh…
Comprehensive Signal Quality Evaluation of a Wearable Textile ECG Garment: A Sex-Balanced Study
Maximilian P. Oppelt, Tobias S. Zech, Sarah H. Lorenz +5
We introduce a novel wearable textile-garment featuring an innovative electrode placement aimed at minimizing noise and motion artifacts, thereby enhancing signal fidelity in Elect…
RadProPoser: Probabilistic Radar Tensor Human Pose Estimation That Knows Its Limits
Jonas Leo Mueller, Lukas Engel, Eva Dorschky +4
Radar-based human pose estimation enables privacy-preserving motion tracking for ambient intelligence, yet the noisy nature of radar sensing makes uncertainty quantification essent…
Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels
Jonathan Ott, Maximilian Stahlke, Tobias Feigl +2
Unsupervised representation learning for wireless channel state information (CSI)reduces reliance on labeled data, thereby lowering annotation costs, and often improves performance…
Understanding Cross-Model Perceptual Invariances Through Ensemble Metamers
Lukas Boehm, Jonas Leo Mueller, Christoffer Loeffler +3
Understanding the perceptual invariances of artificial neural networks is essential for improving explainability and aligning models with human vision. Metamers - stimuli that are…
Robust and Efficient Writer-Independent IMU-Based Handwriting Recognition
Jindong Li, Tim Hamann, Jens Barth +3
Handwriting recognition (HWR) using inertial measurement unit (IMU) data remains challenging due to variations in writing styles and the limited availability of datasets. Previous…
Simultaneous Control of Human Hand Joint Positions and Grip Force via HD-EMG and Deep Learning
Farnaz Rahimi, Mohammad Ali Badamchizadeh, Raul C. Sîmpetru +3
In myoelectric control, simultaneous control of multiple degrees of freedom can be challenging due to the dexterity of the human hand. Numerous studies have focused on hand functio…
Caption-Driven Explorations: Aligning Image and Text Embeddings through Human-Inspired Foveated Vision
Dario Zanca, Andrea Zugarini, Simon Dietz +4
Understanding human attention is crucial for vision science and AI. While many models exist for free-viewing, less is known about task-driven image exploration. To address this, we…
FovEx: Human-Inspired Explanations for Vision Transformers and Convolutional Neural Networks
Mahadev Prasad Panda, Matteo Tiezzi, Martina Vilas +3
Explainability in artificial intelligence (XAI) remains a crucial aspect for fostering trust and understanding in machine learning models. Current visual explanation techniques, su…
Exploring Facial Biomarkers for Detecting Depression through Temporal Analysis of Action Units
Aditya Parikh, Misha Sadeghi, Robert Richer +9
Depression is characterized by persistent sadness and loss of interest, significantly impairing daily functioning and now a widespread mental disorder. Traditional diagnostic metho…
Are LLMs Good Cryptic Crossword Solvers?
Abdelrahman Sadallah, Daria Kotova, Ekaterina Kochmar
Cryptic crosswords are puzzles that rely not only on general knowledge but also on the solver's ability to manipulate language on different levels and deal with various types of wo…
Velocity-Based Channel Charting with Spatial Distribution Map Matching
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprint-based localization improves the positioning performance in challenging, non-line-of-sight (NLoS) dominated indoor environments. However, fingerprinting models require a…
Contrastive Language-Image Pretrained Models are Zero-Shot Human Scanpath Predictors
Dario Zanca, Andrea Zugarini, Simon Dietz +4
Understanding the mechanisms underlying human attention is a fundamental challenge for both vision science and artificial intelligence. While numerous computational models of free-…
From Patches to Objects: Exploiting Spatial Reasoning for Better Visual Representations
Toni Albert, Bjoern Eskofier, Dario Zanca
As the field of deep learning steadily transitions from the realm of academic research to practical application, the significance of self-supervised pretraining methods has become…