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<p>The dynamic vision sensor captures visual information as discrete events, enabling high-speed imaging with reduced data redundancy, but is limited by lack of color sensitivity, a speed-noise trade-off, and inefficient data transfer. Here we show an amphibian-inspired dynamic vision system (ADVS) based on ferroelectric field-effect transistors that emulates the hierarchical functions of amphibian retinas, including spectral perception, spatial preprocessing, and event-driven neural encoding. The ferroelectric transistors exhibit broadband photosensitivity (365–637 nm) and bidirectional photoresponses, enabling multichannel spectral recognition from ultraviolet to visible light. Device arrays further reproduce center–surround receptive-field-like processing, enhancing spatial contrast while suppressing background noise under weak illumination. Owing to the steep switching characteristics (SS<sub>min</sub> = 53.8 mV dec<sup>−1</sup>) of the transistors, the system also supports microsecond-scale event-driven spiking responses. Combined with bioinspired hierarchical preprocessing framework and event-driven convolutional neural network, the ADVS achieves 96.5% accuracy in dynamic facial expression recognition and real-time multi-agent trajectory prediction with &lt;5% error.</p>

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Amphibian-inspired neuromorphic dynamic vision systems based on ferroelectric field-effect transistor

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月23日

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  • Yongbiao Zhai,
  • Peijie Chen,
  • Ying Luo,
  • Ziyu Lv,
  • Guanglong Ding,
  • Junjie Yang,
  • Minglin Zheng,
  • Ye Zhou,
  • Yang Chai,
  • Su-Ting Han

摘要

The dynamic vision sensor captures visual information as discrete events, enabling high-speed imaging with reduced data redundancy, but is limited by lack of color sensitivity, a speed-noise trade-off, and inefficient data transfer. Here we show an amphibian-inspired dynamic vision system (ADVS) based on ferroelectric field-effect transistors that emulates the hierarchical functions of amphibian retinas, including spectral perception, spatial preprocessing, and event-driven neural encoding. The ferroelectric transistors exhibit broadband photosensitivity (365–637 nm) and bidirectional photoresponses, enabling multichannel spectral recognition from ultraviolet to visible light. Device arrays further reproduce center–surround receptive-field-like processing, enhancing spatial contrast while suppressing background noise under weak illumination. Owing to the steep switching characteristics (SSmin = 53.8 mV dec−1) of the transistors, the system also supports microsecond-scale event-driven spiking responses. Combined with bioinspired hierarchical preprocessing framework and event-driven convolutional neural network, the ADVS achieves 96.5% accuracy in dynamic facial expression recognition and real-time multi-agent trajectory prediction with <5% error.