Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866913123967959040 |
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| author | Sadoun, Mohamad Yazan Farsa, Edris Zaman Sharif, Sarah Banad, Yaser Mike |
| author_facet | Sadoun, Mohamad Yazan Farsa, Edris Zaman Sharif, Sarah Banad, Yaser Mike |
| contents | Edge-AI deployment is bottlenecked by data-movement energy; pairing event-driven vision sensors with in-memory analog compute could lift that ceiling by orders of magnitude. Both technologies are individually mature; the framework distinguishing fabricated demonstrations from projected systems is missing. Of six application domains surveyed (robotics, autonomous vehicles, AR/VR, surveillance, medical imaging, IoT), half rest entirely on projection, and existing hardware sits at Technology Readiness Levels 2-5. This evidence-graded review applies a three-paradigm architectural taxonomy and benchmarks the gap against current digital neuromorphic alternatives. It identifies an end-to-end integrated DVS-memristor system as the field's open challenge, with testable accuracy and power targets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_13699 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap Sadoun, Mohamad Yazan Farsa, Edris Zaman Sharif, Sarah Banad, Yaser Mike Hardware Architecture Edge-AI deployment is bottlenecked by data-movement energy; pairing event-driven vision sensors with in-memory analog compute could lift that ceiling by orders of magnitude. Both technologies are individually mature; the framework distinguishing fabricated demonstrations from projected systems is missing. Of six application domains surveyed (robotics, autonomous vehicles, AR/VR, surveillance, medical imaging, IoT), half rest entirely on projection, and existing hardware sits at Technology Readiness Levels 2-5. This evidence-graded review applies a three-paradigm architectural taxonomy and benchmarks the gap against current digital neuromorphic alternatives. It identifies an end-to-end integrated DVS-memristor system as the field's open challenge, with testable accuracy and power targets. |
| title | Memristor Technologies for Dynamic Vision Sensors: A Critical Assessment and Research Roadmap |
| topic | Hardware Architecture |
| url | https://arxiv.org/abs/2605.13699 |