13 citations · 23 across the 4 of their papers we have counts for
5 papers
Accurate and efficient time-domain classification with adaptive spiking recurrent neural networks
Bojian Yin, Federico Corradi, Sander M. Bohte
Inspired by more detailed modeling of biological neurons, Spiking neural networks (SNNs) have been investigated both as more biologically plausible and potentially more powerful mo…
Effective and Efficient Computation with Multiple-timescale Spiking Recurrent Neural Networks
Bojian Yin, Federico Corradi, Sander M. Bohté
The emergence of brain-inspired neuromorphic computing as a paradigm for edge AI is motivating the search for high-performance and efficient spiking neural networks to run on this…
PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing
Diederik Paul Moeys, Daniel Neil, Federico Corradi +7
Machine vision systems using convolutional neural networks (CNNs) for robotic applications are increasingly being developed. Conventional vision CNNs are driven by camera frames at…
Steering a Predator Robot using a Mixed Frame/Event-Driven Convolutional Neural Network
Diederik Paul Moeys, Federico Corradi, Emmett Kerr +5
This paper describes the application of a Convolutional Neural Network (CNN) in the context of a predator/prey scenario. The CNN is trained and run on data from a Dynamic and Activ…
Real time unsupervised learning of visual stimuli in neuromorphic VLSI systems
Massimiliano Giulioni, Federico Corradi, Vittorio Dante +1
Neuromorphic chips embody computational principles operating in the nervous system, into microelectronic devices. In this domain it is important to identify computational primitive…