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Online classification of BCI : Due to both variable trial structure and in order to directly compare with the online classification, we used the recommended default time window length from BCI2000 of…
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The goal is to study DL method for BCI classification:
- [Deep learning with convolutional neural networks for EEG decoding and visualization](https://pubmed.ncbi.nlm.nih.gov/28782865/), 1744 citati…
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A Multi-Branch 3D Convolutional Neural Network for EEG-Based Motor Imagery Classification
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We need people browsing the web to discover interesting datasets than could be added to the moabb.
You can comment on this issue.
But first, check your dataset is not already in [the list](https…
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### Objective
The goal of this issue is to implement a Graph Convolutional Neural Network (GCNs-Net) model for decoding time-resolved EEG motor imagery signals, as outlined in the paper "[GCNs-Net: A…
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Start notebook on explaining the differences in Riemannian Geometric Classification methods. Topics to include:
- [x] Cell for fetching datasets for each individual task using the `eegnb.datasets.d…
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File "/usr/local/lib/python3.5/dist-packages/keras/models.py", line 455, in add
output_tensor = layer(self.outputs[0])
File "/usr/local/lib/python3.5/dist-packages/keras/engine/topology.py", l…
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Collection of interesting papers we find interesting about EEG and SSL
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I am trying to run BCILAB with the following outlines given here
https://docs.google.com/document/d/1iTGj23C5uPW85g4JPDc9l5BTDuKnTvp90y2oCT5JSiY/edit?usp=sharing
As the title suggested it gives …
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Hi there, inspiring method and great paper
have been trying to apply your work on other dataset for couple of days, but cant achieve good results..
recheck the code, i think maybe it's a data-split …