Web: http://arxiv.org/abs/2111.05955

June 24, 2022, 1:11 a.m. | Alex Vicente-Sola, Davide L. Manna, Paul Kirkland, Gaetano Di Caterina, Trevor Bihl

cs.LG updates on arXiv.org arxiv.org

Spiking neural networks (SNNs) have become an interesting alternative to
conventional artificial neural networks (ANN) thanks to their temporal
processing capabilities and energy efficient implementations in neuromorphic
hardware. However the challenges involved in training SNNs have limited their
performance in terms of accuracy and thus their applications. Improving
learning algorithms and neural architectures for a more accurate feature
extraction is therefore one of the current priorities in SNN research. In this
paper we present a study on the key components …

arxiv extraction feature lg networks neural neural networks spiking neural networks

More from arxiv.org / cs.LG updates on arXiv.org

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY