Lee Seokhyeong, Peng Ruoming, Wu Changming, Li Mo
Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, 98195, USA.
Department of Physics, University of Washington, Seattle, WA, 98195, USA.
Nat Commun. 2022 Mar 18;13(1):1485. doi: 10.1038/s41467-022-29171-1.
Image sensors with internal computing capability enable in-sensor computing that can significantly reduce the communication latency and power consumption for machine vision in distributed systems and robotics. Two-dimensional semiconductors have many advantages in realizing such intelligent vision sensors because of their tunable electrical and optical properties and amenability for heterogeneous integration. Here, we report a multifunctional infrared image sensor based on an array of black phosphorous programmable phototransistors (bP-PPT). By controlling the stored charges in the gate dielectric layers electrically and optically, the bP-PPT's electrical conductance and photoresponsivity can be locally or remotely programmed with 5-bit precision to implement an in-sensor convolutional neural network (CNN). The sensor array can receive optical images transmitted over a broad spectral range in the infrared and perform inference computation to process and recognize the images with 92% accuracy. The demonstrated bP image sensor array can be scaled up to build a more complex vision-sensory neural network, which will find many promising applications for distributed and remote multispectral sensing.
具有内部计算能力的图像传感器可实现传感器内计算，这能显著降低分布式系统和机器人技术中机器视觉的通信延迟和功耗。二维半导体因其可调的电学和光学特性以及适合异质集成的特性，在实现此类智能视觉传感器方面具有诸多优势。在此，我们报告一种基于黑磷可编程光电晶体管（bP-PPT）阵列的多功能红外图像传感器。通过电学和光学方式控制栅极介电层中存储的电荷，bP-PPT的电导和光响应性可通过5位精度进行局部或远程编程，以实现传感器内卷积神经网络（CNN）。该传感器阵列可接收在红外波段广泛光谱范围内传输的光学图像，并进行推理计算，以92%的准确率处理和识别图像。所展示的bP图像传感器阵列可扩展以构建更复杂的视觉传感神经网络，这将在分布式和远程多光谱传感方面找到许多有前景的应用。
