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# tf_EEGLearn |
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All implementations are not guaranteed to be correct, have not been checked by original authors, only reimplemented from the paper description and open source code from original authors. |
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## Prerequisites |
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- python >= 3.5 |
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- tensorflow-gpu >= 1.2 |
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- `conda install tensorflow-gpu=1.2` |
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- Numpy |
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- Scipy |
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- Scikit-learn |
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## EEGLearn |
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It's a tensorflow implementation for EEGLearn |
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Bashivan, et al. "Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks." International conference on learning representations (2016). |
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http://arxiv.org/abs/1511.06448 |
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For more information please see https://github.com/pbashivan/EEGLearn |
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<center> |
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</center> |
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## Leave-one-subject-out Experments |
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### Model: EEGLearn |
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| Subject id | S0 | S1 | S2 | S3 | S4 | S5 | S6 | S7 | S8 | S9 | S10 | S11 | S12 | mean | |
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|--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- |--- | |
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| CNN test acc | 55.14 | 73.58 | 93.47 | 100.00 | 100.00 | 99.50 | 99.48 | 100.00 | 98.57 | 100.00 | 98.62 | 72.25 | 49.55 | 87.70 | |