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cs.LG2024
SplitSEE: A Splittable Self-supervised Framework for Single-Channel EEG Representation Learning
Rikuto Kotoge, Zheng Chen, Tasuku Kimura +4
While end-to-end multi-channel electroencephalography (EEG) learning approaches have shown significant promise, their applicability is often constrained in neurological diagnostics…
q-bio.NC2024
Brain-aligning of semantic vectors improves neural decoding of visual stimuli
Shirin Vafaei, Ryohei Fukuma, Takufumi Yanagisawa +10
The development of algorithms to accurately decode neural information has long been a research focus in the field of neuroscience. Brain decoding typically involves training machin…