Vision Transformers, or ViTs, are a groundbreaking learning model designed for tasks in computer vision, particularly image recognition. Unlike CNNs, which use convolutions for image processing, ViTs ...

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Vision Transformers (ViTs) have emerged as a powerful alternative to convolutional neural networks by applying the transformer’s self-attention mechanism directly to image data. In place of sliding ...

“Recent advances in deep learning have promoted EEG decoding for BCI systems, but data sparsity—caused by high costs of EEG collection and inter-subject variability—still limits model performance.