RGB颜色模型
Spike(软件开发)
光电二极管
编码(内存)
光电子学
材料科学
计算机科学
图像传感器
发光二极管
人工智能
动态范围
光学
计算机视觉
物理
软件工程
作者
Ya‐Chi Huang,Y. C. Chen,Kuan‐Ting Chen,Chang‐Hsiao Chen,Li‐Chung Shih,Jen‐Sue Chen
标识
DOI:10.1002/smtd.202401502
摘要
Abstract To enhance the efficiency of machine vision system, physical hardware capable of sensing and encoding is essential. However, sensing and encoding color information has been overlooked. Therefore, this work utilizes an indium‐gallium‐zinc oxide (IGZO) phototransistor to detect varying densities of red, green, and blue (RGB) light, converting them into corresponding drain current (I D ) states. By applying stochastic gate voltage (V G ) pulses to the IGZO phototransistor, the fluctuations are generated in these I D states. When the I D exceeds the threshold current (I TC ), a spike signal is generated. This approach enables the conversion of light densities into spike signals, achieving spike‐rate encoding. Moreover, adjusting the standard deviation (σ) of the V G pulses controls the range of light densities converted into spike rates, while altering the mean (μ) of the V G pulses changes the baseline level of spike rates. Remarkably, separate RGB channels offer a tunable encoding process, which can emphasize individual colors and correct color bias. The encoded spike rates are also fed into a spiking neural network (SNN) for CIFAR‐10 pattern recognition, achieving an accuracy of 86%. The method allows the operation of SNN and shows the tunability in the process of light‐to‐spike encoding, opening possibilities for color image processing.
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