55 citations · 76 across the 7 of their papers we have counts for
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cs.NE2023★ 1 cited
Training a spiking neural network on an event-based label-free flow cytometry dataset
Muhammed Gouda, Steven Abreu, Alessio Lugnan +1
Imaging flow cytometry systems aim to analyze a huge number of cells or micro-particles based on their physical characteristics. The vast majority of current systems acquire a larg…
cs.NE2018
Training Passive Photonic Reservoirs with Integrated Optical Readout
Matthias Freiberger, Andrew Katumba, Peter Bienstman +1
As Moore's law comes to an end, neuromorphic approaches to computing are on the rise. One of these, passive photonic reservoir computing, is a strong candidate for computing at hig…