activity
20212023
most citedKeys to Accurate Feature Extraction Using Residual Spiking Neural Networks

28 citations · 58 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2023★ 1 cited

Frameworks for SNNs: a Review of Data Science-oriented Software and an Expansion of SpykeTorch

Davide Liberato Manna, Alex Vicente-Sola, Paul Kirkland +2

Developing effective learning systems for Machine Learning (ML) applications in the Neuromorphic (NM) field requires extensive experimentation and simulation. Software frameworks a…

cs.CV2022★ 2 cited

Spiking Neural Networks for event-based action recognition: A new task to understand their advantage

Alex Vicente-Sola, Davide L. Manna, Paul Kirkland +2

Spiking Neural Networks (SNN) are characterised by their unique temporal dynamics, but the properties and advantages of such computations are still not well understood. In order to…

cs.NE2022★ 27 cited

Simple and complex spiking neurons: perspectives and analysis in a simple STDP scenario

Davide Liberato Manna, Alex Vicente Sola, Paul Kirkland +2

Spiking neural networks (SNNs) are largely inspired by biology and neuroscience and leverage ideas and theories to create fast and efficient learning systems. Spiking neuron models…

cs.CV2021

Unsupervised Spiking Instance Segmentation on Event Data using STDP

Paul Kirkland, Davide L. Manna, Alex Vicente-Sola +1

Spiking Neural Networks (SNN) and the field of Neuromorphic Engineering has brought about a paradigm shift in how to approach Machine Learning (ML) and Computer Vision (CV) problem…

cs.LG2021★ 28 cited

Keys to Accurate Feature Extraction Using Residual Spiking Neural Networks

Alex Vicente-Sola, Davide L. Manna, Paul Kirkland +2

Spiking neural networks (SNNs) have become an interesting alternative to conventional artificial neural networks (ANN) thanks to their temporal processing capabilities and energy e…