Augmenting Data from Epileptic Brain Seizures Using Deep Generative Networks
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-46238-2_12
Reference41 articles.
1. Abdelhameed, A., & Bayoumi, M. (2021). A Deep learning approach for automatic seizure detection in children with epilepsy. Frontiers in Computational Neuroscience, 15, 650050. https://doi.org/10.3389/fncom.2021.650050
2. Altan, E., Solla, S. A., Miller, L. E., & Perreault, E. J. (2021). Estimating the dimensionality of the manifold underlying multi-electrode neural recordings. PLoS Computational Biology, 17, e1008591. https://doi.org/10.1371/journal.pcbi.1008591
3. Arakaki, T., Barello, G., & Ahmadian, Y. (2017). Capturing the diversity of biological tuning curves using generative adversarial networks. arXiv preprint arXiv:170704582
4. Bear, J., & Lothman, E. W. (1993). An in vitro study of focal epileptogenesis in combined hippocampal-parahippocampal slices. Epilepsy Research, 14, 183–193. https://doi.org/10.1016/0920-1211(93)90043-7
5. Boucher-Routhier, M., & Thivierge, J.-P. (2023). A deep generative adversarial network capturing complex spiral waves in disinhibited circuits of the cerebral cortex. BMC Neuroscience, 24, 22. https://doi.org/10.1186/s12868-023-00792-6
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