activity
20202026
most citedAn empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs

17 citations · 31 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

Tokenization vs. Augmentation: A Systematic Study of Writer Variance in IMU-Based Online Handwriting Recognition

Jindong Li, Dario Zanca, Vincent Christlein +4

Inertial measurement unit-based online handwriting recognition enables the recognition of input signals collected across different writing surfaces but remains challenged by uneven…

cs.CV2026

Enhancing IMU-Based Online Handwriting Recognition via Contrastive Learning with Zero Inference Overhead

Jindong Li, Dario Zanca, Vincent Christlein +4

Online handwriting recognition using inertial measurement units opens up handwriting on paper as input for digital devices. Doing it on edge hardware improves privacy and lowers la…

cs.CV2025

Benchmarking Content-Based Puzzle Solvers on Corrupted Jigsaw Puzzles

Richard Dirauf, Florian Wolz, Dario Zanca +1

Content-based puzzle solvers have been extensively studied, demonstrating significant progress in computational techniques. However, their evaluation often lacks realistic challeng…

cs.LG2024★ 1 cited

Large-Scale Dataset Pruning in Adversarial Training through Data Importance Extrapolation

Björn Nieth, Thomas Altstidl, Leo Schwinn +1

Their vulnerability to small, imperceptible attacks limits the adoption of deep learning models to real-world systems. Adversarial training has proven to be one of the most promisi…

cs.LG2024★ 3 cited

How Intermodal Interaction Affects the Performance of Deep Multimodal Fusion for Mixed-Type Time Series

Simon Dietz, Thomas Altstidl, Dario Zanca +2

Mixed-type time series (MTTS) is a bimodal data type that is common in many domains, such as healthcare, finance, environmental monitoring, and social media. It consists of regular…

eess.SP2023★ 6 cited

Achieving Efficient and Realistic Full-Radar Simulations and Automatic Data Annotation by exploiting Ray Meta Data of a Radar Ray Tracing Simulator

Christian Schüßler, Marcel Hoffmann, Vanessa Wirth +4

In this work a novel radar simulation concept is introduced that allows to simulate realistic radar data for Range, Doppler, and for arbitrary antenna positions in an efficient way…