Faculty of Materials and Manufacturing, Beijing University of Technology, Beijing, 100124, China.
Key Laboratory of Optoelectronics Technology of Education Ministry of China, Faculty of Information Technology, Beijing University of Technology, Beijing, 100124, China.
Adv Mater. 2024 May;36(19):e2312094. doi: 10.1002/adma.202312094. Epub 2024 Feb 13.
Intelligent vision necessitates the deployment of detectors that are always-on and low-power, mirroring the continuous and uninterrupted responsiveness characteristic of human vision. Nonetheless, contemporary artificial vision systems attain this goal by the continuous processing of massive image frames and executing intricate algorithms, thereby expending substantial computational power and energy. In contrast, biological data processing, based on event-triggered spiking, has higher efficiency and lower energy consumption. Here, this work proposes an artificial vision architecture consisting of spiking photodetectors and artificial synapses, closely mirroring the intricacies of the human visual system. Distinct from previously reported techniques, the photodetector is self-powered and event-triggered, outputting light-modulated spiking signals directly, thereby fulfilling the imperative for always-on with low-power consumption. With the spiking signals processing through the integrated synapse units, recognition of graphics, gestures, and human action has been implemented, illustrating the potent image processing capabilities inherent within this architecture. The results prove the 90% accuracy rate in human action recognition within a mere five epochs utilizing a rudimentary artificial neural network. This novel architecture, grounded in spiking photodetectors, offers a viable alternative to the extant models of always-on low-power artificial vision system.
智能视觉需要部署始终开启且低功耗的探测器，以模拟人类视觉的连续不间断响应特性。然而，现代人工视觉系统通过连续处理大量图像帧和执行复杂算法来实现这一目标，从而消耗大量的计算能力和能量。相比之下，基于事件触发尖峰的生物数据处理具有更高的效率和更低的能耗。在这项工作中，提出了一种由尖峰光电探测器和人工突触组成的人工视觉架构，该架构紧密模拟了人类视觉系统的复杂性。与之前报道的技术不同，光电探测器具有自供电和事件触发功能，可直接输出光调制尖峰信号，从而实现低功耗的始终开启功能。通过集成的突触单元处理尖峰信号，已经实现了对图形、手势和人体动作的识别，展示了该架构固有的强大图像处理能力。结果证明，在仅使用基本人工神经网络的五个时期内，人体动作识别的准确率达到 90%。这种基于尖峰光电探测器的新型架构为现有的始终开启低功耗人工视觉系统模型提供了一种可行的替代方案。
