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Owl-vision-inspired near sensor computing

delete2026-02-12
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OA
AI
Z
Zishen Zhao
Y
Yixin Cao
S
Shuaiwei Huang
K
Kaiwen Fan
Y
Yuyao Ding
G
Ganggui Zhu
L
Linhui Li
Q
Qing Liu
W
Wei Deng *
C
Chun Zhao *
M
Mario Lanza *
DOI:10.1038/s41467-026-69123-7delete
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Abstract

Abstract

En 中文
Passive target detection in photon-starved environments is crucial to expand machine vision in a wide range of applications such as precision guidance, intelligent surveillance, and early warning. Here, inspired by owl vision, we report a bimodal synaptic transistor with an optoelectronic decoupling mechanism, enabling parallel photonic perception and electrical plasticity emulation. As a result, the device exhibits a high active adaptation index of approximately 331, alongside the ability to perceive low light intensities as faint as 0.146 nW cm-2. We also achieve cyclically stable synaptic weight modulation with long-term enhancement and inhibition, and verify the feasibility of weight deployment across three basic artificial neural levels over a light intensity range of 0.146-11.70 nW cm-2, via adaptive contrast enhancement. The owl-vision-inspired device establishes a hardware foundation forward in energy-efficient and low-light image processing for neuromorphic vision sensors. Target detection at dark conditions remains a significant challenge. Zhao et al report an owl-vision-inspired dual-mode synaptic transistor, which enables parallel photonic perception and electrical plasticity emulation to achieve light sensitivity surpassing that of conventional CMOS-based vision systems.
Keywords:
Electrical and electronic engineering
Electronic devices
Science
Humanities and Social Sciences
multidisciplinary
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Nature Communications cover
Nature Communications
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15.7
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Fourth Military Medical University
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Xian Jiaotong Liverpool University
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