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Development of GUI Flow Editor Supporting Neuromorphic Architecture Based Neural Network

机译:支持基于神经形态结构的神经网络GUI流编辑器的开发

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As the deep learning model develops, there is a technology called neuromorphic that increases the power consumption efficiency by constructing a circuit similar to a real human neuron. In the existing studies, users can easily create programs using prebuilt components, but many development tools do not support neuromorphic computing models for AI development. Therefore, in this paper, we want to create a development tool that supports the neuromorphic architecture based AI model, and implement the function that the user can directly create a component and add it to the development tool. Through this, we implemented a classifier using spiking neural network (SNN), one of the neuromorphic network models. The classifier evaluated a performance using the well known MNIST model and confirmed that the presented model works as expected.
机译:随着深度学习模型的发展,存在一种称为神经形态的技术,该技术通过构建类似于真实人类神经元的电路来提高功耗效率。在现有研究中,用户可以使用预构建的组件轻松创建程序,但是许多开发工具不支持用于AI开发的神经形态计算模型。因此,在本文中,我们要创建一个支持基于神经形态架构的AI模型的开发工具,并实现用户可以直接创建组件并将其添加到开发工具中的功能。通过这种方式,我们使用尖峰神经网络(SNN)(神经形态网络模型之一)实现了分类器。分类器使用众所周知的MNIST模型评估了性能,并确认提出的模型按预期工作。

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