|
| 基于光致变色钙钛矿材料的非接触式图像识别 |
| Noncontact artificial image recognition based on photochromic perovskite materials |
| 投稿时间：2023-02-28 |
| DOI：10.3969/j.issn.1005-5630.202302280031 |
| 中文关键词: 光致变色材料 钙钛矿 人工突触 图像识别 |
| 英文关键词:photochromic materials perovskite artificial synapse image recognition |
| 基金项目: |
|
| 摘要点击次数: 1941 |
| 全文下载次数: 1683 |
| 中文摘要: |
| 视觉是人类获取信息的主要来源。用于视觉系统模拟的人工图像识别是发展人工智能技术的关键一环。当前，光电突触凭借存算一体式处理光信号的特点被广泛应用于视觉模拟领域，但是突触的光电转换需要对输入光信号进行接触式处理，从而导致大量的能量消耗。针对这个问题，研究了基于光致变色钙钛矿薄膜的全光人工突触，它在紫外和可见光触发下，从光透过率的变化上表现出显著的突触特性，包括配对脉冲易化和学习能力。利用循环神经网络处理随时间变化的透射率数据，实现了对数字图像的二元识别，识别精度从第1个循环就稳定在100%。该器件具有零功耗非接触式信息读取的特点，为视觉系统模拟开辟了一条新的途径。 |
| 英文摘要: |
| Visual perception is the primary source for humans to acquire information. The mimicking of visual systems is crucial to develop artificial intelligence technologies. Currently, optoelectronic synapses are widely used in artificial visual systems due to the in-memory processing of optical signals. However, the photoelectric conversion of the synapses requires contact processing of input optical signals, which leads to significant energy consumption. In this paper, all-optical artificial synapses were presented based on photochromic perovskite thin films. Under UV and visible light pulse stimulation, the perovskite films exhibit synaptic behaviors in optical transmittance changes, including paired-pulse facilitation and learning ability. Through a recurrent neural network processing the time-dependent transmittance change data, a 100% accuracy in the classification of two digital images can be instantly achieved, even in the first epoch. The all-optical synapses provide an innovative pathway toward energy-friendly artificial visual systems. |
| HTML 查看全文 查看/发表评论 下载PDF阅读器 |
| 关闭 |
