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Updated: Apr 10, 2026

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches
Published on: June 21, 2022
Retinocortical in-sensor neuromorphic vision platform for NIR-augmented artificial vision
Jong Bin An1,2, Kyungtae Park3,4, I Sak Lee1,5
1Electronic Device Laboratory, School of Electrical and Electronic Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea.
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.
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