Develops an SNN-integrated personalized federated learning model for BCI brain-signal analysis in immersive communication, reporting highest identification accuracy and 6.46x lower inference energy than ANN baselines.
Framework and overall objectives of the future development of IMT for 2030 and beyond,
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Spiking Personalized Federated Learning for Brain-Computer Interface-Enabled Immersive Communication
Develops an SNN-integrated personalized federated learning model for BCI brain-signal analysis in immersive communication, reporting highest identification accuracy and 6.46x lower inference energy than ANN baselines.