Domain adaptation for time-series classification to mitigate covariate shift

F Ott, D Rügamer, L Heublein, B Bischl… - Proceedings of the 30th …, 2022 - dl.acm.org
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 …

Mm-alt: A multimodal automatic lyric transcription system

X Gu, L Ou, D Ong, Y Wang - Proceedings of the 30th ACM International …, 2022 - dl.acm.org
Automatic lyric transcription (ALT) is a nascent field of study attracting increasing interest
from both the speech and music information retrieval communities, given its significant …

Online handwriting trajectory reconstruction from kinematic sensors using temporal convolutional network

W Swaileh, F Imbert, Y Soullard, R Tavenard… - International Journal on …, 2023 - Springer
Handwriting with digital pens is a common way to facilitate human–computer interaction
through the use of online handwriting (OH) trajectory reconstruction. In this work, we focus …

Deep semi-supervised learning for time-series classification

J Goschenhofer - Deep Learning Applications, Volume 4, 2022 - Springer
While deep semi-supervised learning has gained much attention in computer vision, limited
research exists on its applicability in the time-series domain. In this work, we investigate the …

Auxiliary cross-modal representation learning with triplet loss functions for online handwriting recognition

F Ott, D Rügamer, L Heublein, B Bischl… - IEEE Access, 2023 - ieeexplore.ieee.org
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 …

Uncertainty-aware evaluation of time-series classification for online handwriting recognition with domain shift

A Klaß, SM Lorenz, MW Lauer-Schmaltz… - ar**,
marking omissions, and potential bias in assessment. These issues often arise due to the …

Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition

F Ott, D Rügamer, L Heublein, B Bischl… - … Conference on Pattern …, 2022 - Springer
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. The goal of domain …