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The OnHW Dataset: Online Handwriting Recognition from IMU-enhanced Ballpoint Pens with Machine Learning
F Ott, M Wehbi, T Hamann, J Barth, B Eskofier, C Mutschler
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2020
Овлашћења: Federal Ministry of Education and Research, Germany
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift
F Ott, D Rügamer, L Heublein, B Bischl, C Mutschler
Proceedings of the ACM Multimedia (ACMMM), Lisboa, Portugal, doi: https://dl …, 2022
Овлашћења: Federal Ministry of Education and Research, Germany
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition
F Ott, D Rügamer, L Heublein, B Bischl, C Mutschler
IEEE Access 11 (doi: 10.1109/ACCESS.2023.3310819), pages 94148 - 94172, 2023
Овлашћења: Federal Ministry of Education and Research, Germany
Joint Classification and Trajectory Regression of Online Handwriting Using a Multi-Task Learning Approach
F Ott, D Rügamer, L Heublein, B Bischl, C Mutschler
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022
Овлашћења: Federal Ministry of Education and Research, Germany
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens
F Ott, D Rügamer, L Heublein, T Hamann, J Barth, B Bischl, C Mutschler
International Journal on Document Analysis and Recognition (IJDAR) 25 (12 …, 2022
Овлашћења: Federal Ministry of Education and Research, Germany
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition
F Ott, D Rügamer, L Heublein, B Bischl, C Mutschler
IAPR Intl. Workshop on Multimodal Pattern Recognition of Social Signals in …, 2022
Овлашћења: Federal Ministry of Education and Research, Germany
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