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◆ Nature Communications2026-04-08· Neuromorphic engineering

Retinocortical in-sensor neuromorphic vision platform for NIR-augmented artificial vision

Jong Bin An, Kyungtae Park, I. Sak Lee, Shilin Lu, Hong Gyu Park, Nam Su Heo, Yong Seon Hwang, Kyungmoon Kwak, Kyungho Park, Si‐Hyun Park, J. Lee, Jinkee Hong, Sung Kyu Park, Hyun Jae Kim

原始摘要(英文原文)· Original abstract
In-sensor neuromorphic vision platforms with near-infrared (NIR) sensitivity are essential for intelligent imaging in low-light and multispectral environments. Here, a retinocortical dual-mode platform based on evolved-synaptic transistor (Evo-SynT) devices using upconversion nanoparticles (UCNP) and their integration into evolved-retina optical synapse (EROS) arrays is introduced. Evo-SynT devices exhibit key synaptic features, including paired-pulse facilitation indices exceeding 183.93% and 136.36% at a 0.5 s interval under 808 nm and 940 nm illumination, respectively, and analog weight modulation across 512 conductance states. A 12×12 EROS array enables dual-mode operation: retinal-like in-sensor preprocessing and cortical-like in-memory classification. The EROS array improves pedestrian detection accuracy under low-light conditions from 0.7806 to 0.8481 (808 nm) and 0.9071 (940 nm), and achieves classification accuracies of 77.19% and 79.40%, respectively. These results highlight the EROS platform as a scalable solution for integrated NIR-sensitive neuromorphic vision systems. Current artificial vision systems are less effective beyond the visible spectrum. Here, An et al. report an oxide-semiconductor-based vision platform that enables direct near-infrared signal detection, reliable image enhancement and subsequent image processing under low-light conditions.
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