CBAM-DeepConvNet: Convolutional Block Attention Module-Deep Convolutional Neural Network for asymmetric visual evoked potentials recognition
Purpose: This study aimed to improve the accuracy and the ITR in the stimulative paradigm of character spelling systems based on asymmetric Visual Evoked Potentials (aVEPs) by utilizing EEG signal and an improved Convolutional Block Attention Module-Deep Convolutional Neural Network. Methods: This s...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | Brain-Apparatus Communication |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/27706710.2025.2489396 |
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