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Artificial Optic-neural Synapse Based on Floating-gate Phototransistor for Machine Vision

机译:基于浮栅光电晶体的人工光学 - 神经突出

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The prevailing thrive of artificial neural networks (ANNs) demonstrated their capability especially in cognitive tasks, such as speech recognition, image classification, and natural language processing (NLP). This increased the demands for more power-efficient hardware platform, and resulted in a variety of novel devices were studied to mimic the synaptic dynamics, such as phase change memory (PCM), metal oxide based resistive random access memory (RRAM), ferroelectric field effective transistor (FeFET), and spin transfer torque magnetic random access memory (STT-MRAM). [1] , [2] However, biometric sensing elements are rarely integrated with these synaptic devices. In this work, the artificial optic-neural synapses are emulated by floating-gate phototransistors (FG-PFETs) with InP channels, which enabled the simultaneous sensing and processing of optical information. Clearly, it paved the way toward more systematical hardware integration for machine vision.
机译:人工神经网络(ANNS)的普遍茁壮成长,尤其是在认知任务中的能力,例如语音识别,图像分类和自然语言处理(NLP)。 这增加了对更多节能硬件平台的需求,并导致各种新颖的设备进行了研究以模仿突触动态,例如相变存储器(PCM),金属氧化物基电阻随机存取存储器(RRAM),铁电场 有效的晶体管(FEFET)和旋转转移扭矩磁随机存取存储器(STT-MRAM)。 然而,[2]然而,生物识别感测元件很少与这些突触装置集成。 在这项工作中,通过具有INP通道的浮栅光电晶体管(FG-PFET)仿真人工光学 - 神经突触,其使得能够同时感测和处理光学信息。 显然,它为机器视觉铺平了更加系统化的硬件集成方式。

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