Amiri M, Brooks R, Rivaz H (2020) Fine-tuning u-net for ultrasound image segmentation: different layers, different outcomes. IEEE Trans Ultrason Ferroelectr Freq Control 67(12):2510–2518
Chen X, Wang Y, Gao S, Jung T-P, Gao X (2015) Filter bank canonical correlation analysis for implementing a high-speed ssvep-based brain-computer interface. J Neural Eng 12(4):046008
Chen X, Wang Y, Nakanishi M, Gao X, Jung T-P, Gao S (2015) High-speed spelling with a noninvasive brain-computer interface. Proc Natl Acad Sci 112(44):6058–6067
Chen X, Wang ZJ, McKeown M (2016) Joint blind source separation for neurophysiological data analysis: multiset and multimodal methods. IEEE Signal Proc Mag 33(3):86–107
Chen J, Zhang Y, Pan Y, Xu P, Guan C (2023) A transformer-based deep neural network model for ssvep classification. Neural Netw 164:521–534
Ding W, Shan J, Fang B, Wang C, Sun F, Li X (2021) Filter bank convolutional neural network for short time-window steady-state visual evoked potential classification. IEEE Trans Neural Syst Rehabilitat Eng 29:2615–2624
Ding W, Liu A, Guan L, Chen X (2024) A novel data augmentation approach using mask encoding for deep learning-based asynchronous ssvep-bci. IEEE Trans Neural Syst Rehabilit Eng 32:875–886
Ding W, Liu A, Xie C, Wang K, Chen X (2024) Enhancing domain diversity of transfer learning-based ssvep-bcis by the reconstruction of channel correlation. IEEE Trans Biomed Eng 72:503–514
Dong E, Zhang H, Zhu L, Du S, Tong J (2022) A multi-modal brain-computer interface based on threshold discrimination and its application in wheelchair control. Cognitive Neurodyn 16(5):1123–1133
Gao X, Wang Y, Chen X, Gao S (2021) Interface, interaction, and intelligence in generalized brain-computer interfaces. Trends Cognitive Sci 25(8):671–684
Guney OB, Oblokulov M, Ozkan H (2021) A deep neural network for ssvep-based brain-computer interfaces. IEEE Trans Biomed Eng 69(2):932–944
Jin J, Xiao R, Daly I, Miao Y, Wang X, Cichocki A (2020) Internal feature selection method of csp based on l1-norm and dempster-shafer theory. IEEE Trans Neural Netw Learn Syst 32(11):4814–4825
Jin J, Wang Z, Xu R, Liu C, Wang X, Cichocki A (2021) Robust similarity measurement based on a novel time filter for ssveps detection. IEEE Trans Neural Netw Learn Syst 34(8):4096–4105
Jin J, Xu R, Daly I, Zhao X, Wang X, Cichocki A (2024) Mocnn: a multiscale deep convolutional neural network for erp-based brain-computer interfaces. IEEE Trans Cybernet 54:5565–5576
Kumar A, Raghunathan A, Jones R, Ma T, Liang P (2022) Fine-tuning can distort pretrained features and underperform out-of-distribution. arXiv preprint arXiv:2202.10054
Kwon O-Y, Lee M-H, Guan C, Lee S-W (2019) Subject-independent brain-computer interfaces based on deep convolutional neural networks. IEEE Trans Neural Netw Learn Syst 31(10):3839–3852
LeCun Y, Bengio Y, Hinton G (2015) Deep learning. Nature 521(7553):436–444
Article CAS PubMed Google Scholar
Li P, Su J, Belkacem AN, Cheng L, Chen C (2022) Corrigendum: multi-person feature fusion transfer learning-based convolutional neural network for ssvep-based collaborative bci. Front Neurosci 16:1024150
Article PubMed PubMed Central Google Scholar
Lin Z, Zhang C, Wu W, Gao X (2006) Frequency recognition based on canonical correlation analysis for ssvep-based bcis. IEEE Trans Biomed Eng 53(12):2610–2614
Liu B, Huang X, Wang Y, Chen X, Gao X (2020) Beta: a large benchmark database toward ssvep-bci application. Front Neurosci 14:627
Article PubMed PubMed Central Google Scholar
Liu B, Chen X, Shi N, Wang Y, Gao S, Gao X (2021) Improving the performance of individually calibrated ssvep-bci by task-discriminant component analysis. IEEE Trans Neural Syst Rehabil Eng 29:1998–2007
Luo R, Xu M, Zhou X, Xiao X, Jung T-P, Ming D (2022) Data augmentation of ssveps using source aliasing matrix estimation for brain-computer interfaces. IEEE Trans Biomed Eng 70(6):1775–1785
Nakanishi M, Wang Y, Wang Y-T, Mitsukura Y, Jung T-P (2014) A high-speed brain speller using steady-state visual evoked potentials. Int J Neural Syst 24(06):1450019
Nakanishi M, Wang Y, Chen X, Wang Y-T, Gao X, Jung T-P (2017) Enhancing detection of ssveps for a high-speed brain speller using task-related component analysis. IEEE Trans Biomed Eng 65(1):104–112
Article PubMed PubMed Central Google Scholar
Pan Y, Li N, Zhang Y, Xu P, Yao D (2024) Short-length ssvep data extension by a novel generative adversarial networks based framework. Cognitive Neurodyn. https://doi.org/10.1007/s11571-024-10134-9
Rostami E, Ghassemi F, Tabanfar Z (2023) Transfer learning assisted podnet for stimulation frequency detection in steady state visually evoked potential-based bci spellers. Brain-Computer Interfaces 10(1):38–49
Shao X, Lin M (2020) Filter bank temporally local canonical correlation analysis for short time window ssveps classification. Cognitive Neurodyn 14:689–696
Vaswani A (2017) Attention is all you need. arXiv preprint arXiv:1706.03762
Wan Z, Yang R, Huang M, Zeng N, Liu X (2021) A review on transfer learning in eeg signal analysis. Neurocomputing 421:1–14
Wang Y, Chen X, Gao X, Gao S (2016) A benchmark dataset for ssvep-based brain-computer interfaces. IEEE Trans Neural Syst Rehabil Eng 25(10):1746–1752
Wang Z, Wong CM, Rosa A, Qian T, Jung T-P, Wan F (2022) Stimulus-stimulus transfer based on time-frequency-joint representation in ssvep-based bcis. IEEE Trans Biomed Eng 70(2):603–615
Wang X, Liu A, Wu L, Guan L, Chen X (2023) Improving generalized zero-shot learning ssvep classification performance from data-efficient perspective. IEEE Trans Neural Syst Rehabil Eng 31:4135–4145
Wang X, Liu A, Wu L, Li C, Liu Y, Chen X (2023) A generalized zero-shot learning scheme for ssvep-based bci system. IEEE Trans Neural Syst Rehabil Eng 31:863–874
Waytowich N, Lawhern VJ, Garcia JO, Cummings J, Faller J, Sajda P, Vettel JM (2018) Compact convolutional neural networks for classification of asynchronous steady-state visual evoked potentials. J Neural Eng 15(6):066031
Wong CM, Wang Z, Wang B, Lao KF, Rosa A, Xu P, Jung T-P, Chen CP, Wan F (2020) Inter-and intra-subject transfer reduces calibration effort for high-speed ssvep-based bcis. IEEE Trans Neural Syst Rehabil Eng 28(10):2123–2135
Wu D, Xu Y, Lu B-L (2020) Transfer learning for eeg-based brain-computer interfaces: a review of progress made since 2016. IEEE Trans Cognitive Dev Syst 14(1):4–19
Xiao R, Huang Y, Xu R, Wang B, Wang X, Jin J (2022) Coefficient-of-variation-based channel selection with a new testing framework for mi-based bci. Cognitive Neurodyn. https://doi.org/10.1007/s11571-021-09752-4
Xiong H, Song J, Liu J, Han Y (2024) Deep transfer learning-based ssvep frequency domain decoding method. Biomed Signal Proc Control 89:105931
Xiong B, Wan B, Huang J, Li F, Li X, Yang P (2024) Cross-stimulus transfer method using common impulse response for fast calibration of ssvep-based bcis. IEEE Trans Instrum Measurement. https://doi.org/10.1109/TIM.2024.3374314
Xu L, Xu M, Jung T-P, Ming D (2021) Review of brain encoding and decoding mechanisms for eeg-based brain-computer interface. Cognitive Neurodyn 15:569–584
Yin X, Lin M (2024) Multi-information improves the performance of cca-based ssvep classification. Cognitive Neurodyn 18(1):165–172
Comments (0)