The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Single-trial EEG classification of motor imagery using deep convolutional neural networks
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Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805
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Oldfield, R. C. (1971) · Neuropsychologia · doi:10.1016/0028-3932(71)90067-4 · Cited by 35,900
Event-related EEG/MEG synchronization and desynchronization: basic principles
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Multi-column deep neural networks for image classification
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A review of classification algorithms for EEG-based brain–computer interfaces
Lotte, F., Congedo, M., Lécuyer, A., Lamarche, F., & Arnaldi, B. (2007) · Journal of Neural Engineering · doi:10.1088/1741-2560/4/2/r01 · Cited by 2,665
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Deep learning with convolutional neural networks for EEG decoding and visualization
Schirrmeister, R. T., Springenberg, J. T., Fiederer, L. D. J., Glasstetter, M., Eggensperger, K., Tangermann, M., Hutter, F., Burgard, W., & Ball, T. (2017) · Human Brain Mapping · doi:10.1002/hbm.23730 · Cited by 3,751
Deep learning for electroencephalogram (EEG) classification tasks: a review
Craik, A., He, Y., & Contreras-Vidal, J. L. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab0ab5 · Cited by 1,758
Deep learning-based electroencephalography analysis: a systematic review
Roy, Y., Banville, H., Albuquerque, I., Gramfort, A., Falk, T. H., & Faubert, J. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab260c · Cited by 1,532
An end-to-end deep learning approach to MI-EEG signal classification for BCIs
Dose, H., Møller, J. S., Iversen, H. K., & Puthusserypady, S. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2018.08.031 · Cited by 382
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Zhang, X., Yao, L., Wang, X., Monaghan, J., McAlpine, D., & Zhang, Y. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abc902 · Cited by 296
Metadata
- Authors
- Tang, Z., Li, C., & Sun, S.
- Venue
- Optik
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 130
- Pages
- 11-18
- ISSN
- 0030-4026 (ISSN-L)
- OpenAlex
- W2551178936
- Cited by
- 299
- References
- 26
- FWCI
- 14.89
- Type
- journal article
- Language
- en
- Open access
- closed
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- Tang, Z., Li, C., & Sun, S. (2017). Single-trial EEG classification of motor imagery using deep convolutional neural networks. Optik. https://doi.org/10.1016/j.ijleo.2016.10.117
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
