A comparative review of deep and spiking neural networks for edge AI neuromorphic circuits Article Swipe
Pietro M. Ferreira
,
Siqi Wang
,
Y. Gao
,
Aziz Benlarbi‐Delaï
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fnins.2025.1676570
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/fnins.2025.1676570
Edge AI implements neural networks directly in electronic circuits, using either deep neural networks (DNNs) or neuromorphic spiking neural networks (SNNs). DNNs offer high accuracy and easy-to-use tools but are computationally intensive and consume significant power. SNNs utilize bio-inspired, event-driven architectures that can be significantly more energy-efficient, but they rely on less mature training tools. This review surveys digital and analog edge-AI implementations, outlining device architectures, neuron models, and trade-offs in energy (J/OP), area (μm 2 /OP), and integration technology.
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Metadata
- Type
- review
- Language
- en
- Landing Page
- https://doi.org/10.3389/fnins.2025.1676570
- https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1676570/pdf
- OA Status
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- Cited By
- 1
- References
- 28
- OpenAlex ID
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https://doi.org/10.3389/fnins.2025.1676570Digital Object Identifier
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A comparative review of deep and spiking neural networks for edge AI neuromorphic circuitsWork title
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enPrimary language
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2025Year of publication
- Publication date
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2025-10-02Full publication date if available
- Authors
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Pietro M. Ferreira, Siqi Wang, Y. Gao, Aziz Benlarbi‐DelaïList of authors in order
- Landing page
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https://doi.org/10.3389/fnins.2025.1676570Publisher landing page
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https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1676570/pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2025.1676570/pdfDirect OA link when available
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1Total citation count in OpenAlex
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2025: 1Per-year citation counts (last 5 years)
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28Number of works referenced by this work
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