most citedISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks

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cs.NE2025★ 1 cited

ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks

Junyan Li, Bin Hu, Zhi-Hong Guan

Cross-subject variability in EEG degrades performance of current deep learning models, limiting the development of brain-computer interface (BCI). This paper proposes ISAM-MTL, whi…

cs.NE2024

AM-MTEEG: Multi-task EEG classification based on impulsive associative memory

Junyan Li, Bin Hu, Zhi-Hong Guan

Electroencephalogram-based brain-computer interface (BCI) has potential applications in various fields, but their development is hindered by limited data and significant cross-indi…