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Computer Science
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Turns out, you can predict what drivers will do next with surprising accuracy (90%) using EEG data, even in messy, real-world driving conditions.
ShallowConvNet emerges as a surprisingly effective architecture for decoding user intent from EEG signals in real-world robotic control, outperforming more complex models like Transformers.
