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Photoreceptors and Visual Pathways01:22

Photoreceptors and Visual Pathways

At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category, whereas...

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Neuromorphic Visual Computing with ZnMgO QDs-Based UV-Responsive Optoelectronic Synaptic Devices for Image Encryption

Zilong Guo1, Hao Kan1, Jiaqi Zhang2

  • 1Shandong Provincial Key Laboratory of Ubiquitous Intelligent Computing, School of Information Science and Engineering, University of Jinan, Jinan, 250022, China.

Small (Weinheim an Der Bergstrasse, Germany)
|March 4, 2025
PubMed
Summary

Researchers developed a UV-responsive optoelectronic synaptic device using ZnMgO quantum dots for neuromorphic vision. This device enables in-sensor computing, image encryption, and robust image recognition, advancing artificial visual perception.

Keywords:
UV‐responsiveZnMgO QDsimage processingneuromorphic visual computingoptoelectronic synaptic device

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Area of Science:

  • Optoelectronics and Neuromorphic Engineering
  • Materials Science for Advanced Computing

Background:

  • Neuromorphic visual computing relies on retina-inspired optoelectronic devices for integrated sensing and computation.
  • Ultraviolet (UV)-responsive optoelectronic synaptic devices are crucial for enhancing visual perception in advanced systems.

Purpose of the Study:

  • To demonstrate a novel UV-responsive optoelectronic synaptic device utilizing ZnMgO quantum dots (QDs).
  • To explore the device's potential for in-sensor computing in neuromorphic vision applications, including image encryption and reservoir computing.

Main Methods:

  • Fabrication of a UV-responsive optoelectronic synaptic device based on ZnMgO QDs.
  • Characterization of voltage-driven short-term and long-term synaptic plasticity and photoinduced synaptic functions.
  • Development of an in-sensor image-blending encryption method and a reservoir computing (RC) system with a photonic reservoir layer (PRL) and multilayer perceptron (MLP).

Main Results:

  • The device exhibited voltage-driven synaptic plasticity and multiple photoinduced synaptic functions.
  • An in-sensor image-blending encryption method was successfully designed to mitigate data leakage risks.
  • The constructed RC system achieved 98.6% accuracy on Fashion-MNIST recognition, maintaining 83% accuracy under 60% noise.

Conclusions:

  • The developed ZnMgO QD-based device offers a novel approach for UV-responsive optoelectronic synaptic functions.
  • The dual-mode modulation (electrical and optical signals) provides new solutions for integrated neuromorphic vision systems.
  • This work advances the development of robust and efficient in-sensor computing for artificial vision.