Deep learning based on Batch Normalization for P300 signal detection

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A few filters are enough: Convolutional Neural Network for P300 DetectionPreprint

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Toward Lightweight, Efficient, and Explainable Deep Learning Models for P300 Detection

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Trend-Aware Multiscale Spatial-Temporal Graph Convolution Network for P300 Detection

Wang, J., Zheng, W., Zong, Y., & Zhou, X. (2026) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2025.3645356 · Cited by 1

Error perception classification in Brain-Computer Interfaces using CNN

Correia, J. R., Sanches, J., & Mainardi, L. T. (2021) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc46164.2021.9631080 · Cited by 1

EEG recognition model based on wavelet packet decomposition and ConvNet for art design decisions

Yang, B., Liao, J., Yang, J., & Zhang, W. (2023) · Engineering Research Express · doi:10.1088/2631-8695/acd73d · Cited by 1

An Unsupervised Feature Extraction Method based on CLSTM-AE for Accurate P300 Classification in Brain-Computer Interface Systems

Afrah, R., Amini, Z., & Kafieh, R. (2023) · Journal of Biomedical Physics and Engineering · doi:10.31661/jbpe.v0i0.2207-1521 · Cited by 1

Comparative Evaluation of Facial Paradigms for Devanagari Script-Based P300 Speller: Preliminary Findings

Bhandari, V., Londhe, N. D., & Kshirsagar, G. B. (2024) · Journal of Data Science and Intelligent Systems · doi:10.47852/bonviewjdsis42021463 · Cited by 1

Automated Motor Imagery Detection Through EEG Analysis and Deep Learning Models for Brain-Computer Interface Applications

Li, Y., Liu, B., & Tian, Y. (2024) · International Journal of Advanced Computer Science and Applications · doi:10.14569/ijacsa.2024.0150514 · Cited by 1

A Novel Parameter-Free Attention-based Multiscale Convolution Prototype Networks for P300 Brain-computer Interface

Wang, J., Wang, F., Yan, H., & Zheng, Z. (2024) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn60899.2024.10650125 · Cited by 1

A Stacked Autoencoders Approach for a P300 Speller BCI

Ghazikhani, H., & Rouhani, M. (2018) · International Conference on Computer and Knowledge Engineering · doi:10.1109/iccke.2018.8566534 · Cited by 1

A Convolutional Neural Network based on Batch Normalization and Residual Block for P300 Signal Detection of P300-speller System

Lu, Z., Li, Q., Gao, N., Wang, T., Yang, J., & Bai, O. (2019) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2019.8816214 · Cited by 10

Fusion of Convolutional Neural Networks for P300 Based Character Recognition

Kundu, S., & Ari, S. (2019) · doi:10.1109/icit48102.2019.00034 · Cited by 12

Towards Effective Deep Neural Network Approach for Multi-Trial P300-Based Character Recognition in Brain-Computer Interfaces

Shukla, P. K., Cecotti, H., & Meena, Y. K. (2024) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/smc54092.2024.11169725 · Cited by 1

Spelling Detection based on P300 Signal with Convolutional Neural Network (CNN) Algorithm

Muharrom, K. M. R., & Primartha, R. (2022) · Sriwijaya Journal of Informatics and Applications · doi:10.36706/sjia.v3i1.38

Convolutional Neural Networks for P300 Detection with Application to Brain-Computer Interfaces

Cecotti, H., & Graser, A. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2010.125 · Cited by 778