https://github.com/alexander-jing/deeptransferbci
Science Score: 26.0%
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Low similarity (4.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Alexander-Jing
- Language: Python
- Default Branch: main
- Size: 301 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Deep Transfer Learning for Brain Computer Interface (DeepTransferBCI)
We are trying to implement our methods about the online adaptive decoding algorithms via EEG or fNIRS in this repo, codes coming soon.
References
Codes referring to the following repos and papers:
Repos:
DeepTransferEEG: https://github.com/sylyoung/DeepTransferEEG
fNIRS-mental-workload-classifiers: https://github.com/tufts-ml/fNIRS-mental-workload-classifiers
BENDR: https://github.com/SPOClab-ca/BENDR
Papers:
Li S, Wang Z, Luo H, et al. T-TIME: Test-time information maximization ensemble for plug-and-play BCIs[J]. IEEE Transactions on Biomedical Engineering, 2023.
Huang Z, Wang L, Blaney G, et al. The tufts fnirs mental workload dataset & benchmark for brain-computer interfaces that generalize[C]//Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2). 2021.
Kostas D, Aroca-Ouellette S, Rudzicz F. BENDR: Using transformers and a contrastive self-supervised learning task to learn from massive amounts of EEG data[J]. Frontiers in Human Neuroscience, 2021, 15: 653659.
Owner
- Name: Jing
- Login: Alexander-Jing
- Kind: user
- Location: Beijing
- Company: CASIA
- Repositories: 2
- Profile: https://github.com/Alexander-Jing
UCAS
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- Push event: 35
Last Year
- Push event: 35