基于强化学习的神经形态系统彩色图像分类

2020 International Conference on Electronics, Information, and Communication (ICEIC) Pub Date : 2020-01-01 DOI:10.1109/ICEIC49074.2020.9051310

Junhee Park, Sumin Jo, Jungwon Lee, Wookyung Sun

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引用次数: 2

摘要

研究了基于二元单色数值数据的神经形态硬件系统。在本研究中，神经形态硬件系统的输入使用二色图像而不是单色图像。彩色图像分类采用强化学习实现。此外，我们还对突触权值的较小自由度进行了实验，以实现一个二元神经形态硬件系统。通过本研究可以开发更复杂的彩色图像分类。

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Color image classification on neuromorphic system using reinforcement learning

Neuromorphic hardware system has been studied based on binary monochromatic numerical data. In this study, the input to neuromorphic hardware systems uses binary color images rather than monochrome. Color image classification is implemented using reinforcement learning. In addition, the smaller degree of freedom of synaptic weights is experimented to implement a binary neuromorphic hardware system. More complicated color image classification can be developed with this study.

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2020 International Conference on Electronics, Information, and Communication (ICEIC)

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