EEG Denoising
2 papers with code • 0 benchmarks • 0 datasets
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Most implemented papers
EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising
Here, we present EEGdenoiseNet, a benchmark EEG dataset that is suited for training and testing deep learning-based denoising models, as well as for performance comparisons across models.
Embedding Decomposition for Artifacts Removal in EEG Signals
DeepSeparator employs an encoder to extract and amplify the features in the raw EEG, a module called decomposer to extract the trend, detect and suppress artifact and a decoder to reconstruct the denoised signal.