Robin Tibor Schirrmeister
59 linhas
1.6 KiB
ReStructuredText
59 linhas
1.6 KiB
ReStructuredText
Note: The old braindecode repository has been moved to
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https://github.com/robintibor/braindevel.
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Braindecode
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===========
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A deep learning toolbox to decode raw time-domain EEG.
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For EEG researchers that want to want to work with deep learning and
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deep learning researchers that want to work with EEG data.
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For now focussed on convolutional networks.
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Installation
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============
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1. Install pytorch from http://pytorch.org/ (you don't need to install torchvision).
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2. Install numpy (necessary for resamply installation to work), e.g.:
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.. code-block:: bash
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pip install numpy
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3. Install braindecode via pip:
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.. code-block:: bash
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pip install braindecode
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Documentation
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=============
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Documentation is online under https://robintibor.github.io/braindecode/
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Citing
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======
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If you use this code in a scientific publication, please cite us as:
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.. code-block:: bibtex
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@article {HBM:HBM23730,
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author = {Schirrmeister, Robin Tibor and Springenberg, Jost Tobias and Fiederer,
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Lukas Dominique Josef and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and
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Hutter, Frank and Burgard, Wolfram and Ball, Tonio},
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title = {Deep learning with convolutional neural networks for EEG decoding and visualization},
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journal = {Human Brain Mapping},
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issn = {1097-0193},
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url = {http://dx.doi.org/10.1002/hbm.23730},
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doi = {10.1002/hbm.23730},
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month = {aug},
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year = {2017},
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keywords = {electroencephalography, EEG analysis, machine learning, end-to-end learning, brain–machine interface,
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brain–computer interface, model interpretability, brain mapping},
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}
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