5 papers · 1 filter
Rectifying Geometric Misalignment: Online Source-Free Adaptation for Class-Imbalanced EEG
Shiwen Chu, Shanglin Li, Motoaki Kawanabe +1
Electroencephalography (EEG) based Brain-Computer Interfaces (BCIs) often require unsupervised domain adaptation (UDA) to generalize across subjects and sessions. While Riemannian…
EEG-Based Multimodal Learning via Hyperbolic Mixture-of-Curvature Experts
Runhe Zhou, Shanglin Li, Guanxiang Huang +5
Electroencephalography (EEG)-based multimodal learning integrates brain signals with complementary modalities to improve mental state assessment, providing great clinical potential…
HEEGNet: Hyperbolic Embeddings for EEG
Shanglin Li, Shiwen Chu, Okan Koç +4
Electroencephalography (EEG)-based brain-computer interfaces facilitate direct communication with a computer, enabling promising applications in human-computer interactions. Howeve…
An Automated Pipeline for Few-Shot Bird Call Classification: A Case Study with the Tooth-Billed Pigeon
Abhishek Jana, Moeumu Uili, James Atherton +3
This paper presents a largely automated one-shot bird call classification pipeline, incorporating targeted manual quality control steps, designed for rare species absent from large…
On the interpretation of linear Riemannian tangent space model parameters in M/EEG
Reinmar J. Kobler, Jun-Ichiro Hirayama, Lea Hehenberger Catarina Lopes-Dias +2
Riemannian tangent space methods offer state-of-the-art performance in magnetoencephalography (MEG) and electroencephalography (EEG) based applications such as brain-computer inter…