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Revisiting Batch Normalization for Training Low-Latency Deep Spiking Neural Networks From Scratch
Spiking Neural Networks (SNNs) have recently emerged as an alternative to deep learning owing to sparse, asynchronous and binary event (or spike) driven processing, that can yield huge energy efficiency benefits on neuromorphic hardware. However, SNNs convey temporally-varying spike activation throu...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Frontiers Media S.A.
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8695433/ https://www.ncbi.nlm.nih.gov/pubmed/34955725 http://dx.doi.org/10.3389/fnins.2021.773954 |