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Found 6 papers, 1 papers with code
Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data
Jamming devices pose a significant threat by disrupting signals from the global navigation satellite system (GNSS), compromising the robustness of accurate positioning.
Fusing Structure from Motion and Simulation-Augmented Pose Regression from Optical Flow for Challenging Indoor Environments
In this work, we propose recurrent fusion networks to optimally align absolute and relative pose predictions to improve the absolute pose prediction.
Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition
The goal of domain adaptation (DA) is to mitigate this domain shift problem by searching for an optimal feature transformation to learn a domain-invariant representation.
Domain Adaptation for Time-Series Classification to Mitigate Covariate Shift
To mitigate this domain shift problem, domain adaptation (DA) techniques search for an optimal transformation that converts the (current) input data from a source domain to a target domain to learn a domain-invariant representation that reduces domain discrepancy.
Auxiliary Cross-Modal Representation Learning with Triplet Loss Functions for Online Handwriting Recognition
We perform extensive evaluations on synthetic image and time-series data, and on data for offline handwriting recognition (HWR) and on online HWR from sensor-enhanced pens for classifying written words.
Benchmarking Online Sequence-to-Sequence and Character-based Handwriting Recognition from IMU-Enhanced Pens
While there exist many offline HWR datasets, there is only little data available for the development of OnHWR methods on paper as it requires hardware-integrated pens.
