428 citations · 4.5k across the 191 of their papers we have counts for
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Exploring Embedding Methods in Binary Hyperdimensional Computing: A Case Study for Motor-Imagery based Brain-Computer Interfaces
Michael Hersche, José del R. Millán, Luca Benini +1
Key properties of brain-inspired hyperdimensional (HD) computing make it a prime candidate for energy-efficient and fast learning in biosignal processing. The main challenge is how…
One-shot Learning for iEEG Seizure Detection Using End-to-end Binary Operations: Local Binary Patterns with Hyperdimensional Computing
Alessio Burrello, Kaspar Schindler, Luca Benini +1
This paper presents an efficient binarized algorithm for both learning and classification of human epileptic seizures from intracranial electroencephalography (iEEG). The algorithm…
Fast and Accurate Multiclass Inference for MI-BCIs Using Large Multiscale Temporal and Spectral Features
Michael Hersche, Tino Rellstab, Pasquale Davide Schiavone +3
Accurate, fast, and reliable multiclass classification of electroencephalography (EEG) signals is a challenging task towards the development of motor imagery brain-computer interfa…
PULP-HD: Accelerating Brain-Inspired High-Dimensional Computing on a Parallel Ultra-Low Power Platform
Fabio Montagna, Abbas Rahimi, Simone Benatti +2
Computing with high-dimensional (HD) vectors, also referred to as , is a brain-inspired alternative to computing with scalars. Key properties of HD computing…