Jul 8, 2021 · Experimental results demonstrate that EEG-ConvTransformer achieves improved classification accuracy over the state-of-the-art techniques across ...
This work introduces an EEG-ConvTranformer network that is based on both multi-headed self-attention and temporal convolution.
This work introduces an EEG-ConvTranformer network that is based on both multi-headed self-attention and temporal convolution.
This is a community implemention of arcticle: [1] Bagchi S, Bathula D R. EEG-ConvTransformer for single-trial EEG-based visual stimulus classification[J].
Jul 8, 2021 · Experimental results demonstrate that EEG-ConvTransformer achieves improved classification accuracy over the state-of-the-art techniques across ...
Oct 22, 2024 · Experimental results demonstrate that EEG-ConvTransformer achieves improved classification accuracy over state-of-the-art techniques across five ...
Jul 8, 2021 · EEG-ConvTransformer achieves improved classification accuracy over the state-of-the-art techniques across five different visual stimuli classification tasks.
This is a community implemention of arcticle: [1] Bagchi S, Bathula D R. EEG-ConvTransformer for single-trial EEG-based visual stimulus classification[J].
Jul 8, 2021 · Experimental results demonstrate that EEG-ConvTransformer achieves improved classification accuracy over the state-of-the-art techniques across ...
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EEG-ConvTransformer for single-trial EEG-based visual stimulus ...
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Highlights：. • Introduces EEG-ConvTransformer to improve EEG-based visual stimulus classification. • Leverages spatial context using inter-region ...