Search Results for author:
Found 3 papers, 1 papers with code
Fusing Pretrained ViTs with TCNet for Enhanced EEG Regression
The task of Electroencephalogram (EEG) analysis is paramount to the development of Brain-Computer Interfaces (BCIs).
ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data
In this study, we demonstrate the application of a hybrid Vision Transformer (ViT) model, pretrained on ImageNet, on an electroencephalogram (EEG) regression task.
Two Heads are Better than One: A Bio-inspired Method for Improving Classification on EEG-ET Data
Classifying EEG data is integral to the performance of Brain Computer Interfaces (BCI) and their applications.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
