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Title: GitHub - snailpt/CTNet: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification · GitHub

Open Graph Title: GitHub - snailpt/CTNet: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

X Title: GitHub - snailpt/CTNet: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

Description: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification - snailpt/CTNet

Open Graph Description: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification - snailpt/CTNet

X Description: CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification - snailpt/CTNet

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Opengraph URL: https://github.com/snailpt/CTNet

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LICENSE	https://github.com/snailpt/CTNet/blob/main/LICENSE
LICENSE	https://github.com/snailpt/CTNet/blob/main/LICENSE
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utils.py	https://github.com/snailpt/CTNet/blob/main/utils.py
utils.py	https://github.com/snailpt/CTNet/blob/main/utils.py
README	https://github.com/snailpt/CTNet
MIT license	https://github.com/snailpt/CTNet
	https://github.com/snailpt/CTNet#ctnet-for-motor-imagery-eeg-classification
Paper	https://www.nature.com/articles/s41598-024-71118-7
	https://github.com/snailpt/CTNet#ctnet-a-convolutional-transformer-network-for-eeg-based-motor-imagery-classification-paper
EEG Conformer	https://github.com/eeyhsong/EEG-Conformer
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BCI IV-2a	https://www.bbci.de/competition/iv/results/ds2a/true_labels.zip
BCI IV-2b	https://www.bbci.de/competition/iv/results/ds2b/true_labels.zip
	https://github.com/snailpt/CTNet#preprocessing-dataset-merge-data-and-labels-to-create-a-dataloader-for-training-the-model-edf---mat
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	https://github.com/snailpt/CTNet#under-the-loso-setting-if-data-augmentation-is-required-it-is-recommended-to-refer-to-the-updated-training-framework-code-in-which-the-data-augmentation-pipeline-has-been-optimized-specifically-sr-performs-data-augmentation-on-each-subject-in-the-training-set-one-by-one-and-then-concatenates-the-data-from-different-subjects-to-construct-the-training-set-refer-to-the-loso-code-of-tcanet-httpsgithubcomsnailpttcanetblobmainloso_tcanetipynb
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https://doi.org/10.1038/s41598-024-71118-7	https://doi.org/10.1038/s41598-024-71118-7
	https://github.com/snailpt/CTNet#communication
www.nature.com/articles/s41598-024-71118-7	https://www.nature.com/articles/s41598-024-71118-7
cnn	https://github.com/topics/cnn
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