36 citations · 202 across the 35 of their papers we have counts for
9 papers · 1 filter
Indoor Localization with Robust Global Channel Charting: A Time-Distance-Based Approach
Maximilian Stahlke, George Yammine, Tobias Feigl +2
Fingerprinting-based positioning significantly improves the indoor localization performance in non-line-of-sight-dominated areas. However, its deployment and maintenance is cost-in…
Towards Realistic Statistical Channel Models For Positioning: Evaluating the Impact of Early Clusters
Mohammad Alawieh, George Yammine, Ernst Eberlein +5
Physical effects such as reflection, refraction, and diffraction cause a radio signal to arrive from a transmitter to a receiver in multiple replicas that have different amplitude…
Complementary Semi-Deterministic Clusters for Realistic Statistical Channel Models for Positioning
Mohammad Alawieh, Ernst Eberlein, Stephan Jäckel +5
Positioning benefits from channel models that capture geometric effects and, in particular, from the signal properties of the first arriving path and the spatial consistency of the…
Benchmarking Visual-Inertial Deep Multimodal Fusion for Relative Pose Regression and Odometry-aided Absolute Pose Regression
Felix Ott, Nisha Lakshmana Raichur, David Rügamer +4
Visual-inertial localization is a key problem in computer vision and robotics applications such as virtual reality, self-driving cars, and aerial vehicles. The goal is to estimate…
Uncertainty-aware Evaluation of Time-Series Classification for Online Handwriting Recognition with Domain Shift
Andreas Klaß, Sven M. Lorenz, Martin W. Lauer-Schmaltz +4
For many applications, analyzing the uncertainty of a machine learning model is indispensable. While research of uncertainty quantification (UQ) techniques is very advanced for com…
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift
Felix Ott, David Rügamer, Lucas Heublein +2
The performance of a machine learning model degrades when it is applied to data from a similar but different domain than the data it has initially been trained on. To mitigate this…
Position Tracking using Likelihood Modeling of Channel Features with Gaussian Processes
Sebastian Kram, Christopher Kraus, Tobias Feigl +3
Recent localization frameworks exploit spatial information of complex channel measurements (CMs) to estimate accurate positions even in multipath propagation scenarios. State-of-th…
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition
Felix Ott, David Rügamer, Lucas Heublein +2
Cross-modal representation learning learns a shared embedding between two or more modalities to improve performance in a given task compared to using only one of the modalities. Cr…
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens
Felix Ott, David Rügamer, Lucas Heublein +4
Purpose. Handwriting is one of the most frequently occurring patterns in everyday life and with it come challenging applications such as handwriting recognition (HWR), writer ident…