基于Mott Memristor的人工视觉神经元的近红外和紫外线图像的融合
Wanlin Zhang1, Jiayi Mao2, Dingwei Li2
1State Key Laboratory of Wide Band Gap Semiconductor Devices and Integrated Technology, School of Microelectronics, Xidian University, Xi'an, 710071, China.
Small (Weinheim an der Bergstrasse, Germany)
|August 21, 2025
概括
研究人员开发了一种新型的人工视觉神经元, 这种生物灵感系统集成了紫外线和近红外线数据,
科学领域:
- 材料科学
- 神经科学
- 计算机科学
背景情况:
- 生物系统通过多频段数据集成实现全面的图像理解.
- 开发高效,低功耗的人工视觉系统用于多频段图像融合仍然是一个重大挑战.
研究的目的:
- 提出并展示一种能够进行多频段传感和图像融合的人工视觉神经元.
- 创建一个生物启发的人工视觉系统,
主要方法:
- 整合一个In2O3/PY-IT光传感器和一个NbOx Mott记忆器来创建一个人工视觉神经元.
- 使用光强度来控制不同频谱的脉冲编码频率.
- 使用脉冲合神经网络 (PCNN) 来处理编码的脉冲信号并执行图像融合.
主要成果:
- 人工视觉神经元成功地感知了紫外线和近红外波段的光学信号.
- 该系统能够将光强度的变化编码为不同的脉冲频率.
- 在不同的照明条件下,PCNN成功地融合了多频段图像信息,展示了生物功能.
结论:
- 拟议的人工视觉神经元是整合,功能和低功耗的人工视觉系统的关键组成部分.
- 这项工作为以生物视觉为灵感的基于硬件的多频段感知系统提供了基础.
- 开发的系统为人工视觉应用提供了一种高效的多频段图像融合的新方法.
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