28 citations · 28 across the 3 of their papers we have counts for
4 papers
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…
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…
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…
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…