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Human recognition of a partner robot based on relevance theory and neuro-fuzzy computing

机译:基于关联理论和神经模糊计算的合作伙伴机器人的人为识别

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This paper proposes a human recognition method of a partner robot for natural communication with human. Basically, human recognition is performed by using various types of information. In this paper, we use the color image of human face and pattern of conversation with the human. The proposed method is composed of k-means algorithm, spiking neural network, self-organizing map, and steady-state genetic algorithm. Furthermore, we show experimental results of the partner robot based on the proposed method.
机译:本文提出了一种与人自然交流的伙伴机器人的人为识别方法。基本上,通过使用各种类型的信息来执行人类识别。在本文中,我们使用人脸的彩色图像和与人交谈的模式。该方法由k均值算法,尖峰神经网络,自组织图和稳态遗传算法组成。此外,我们展示了基于提出的方法的伙伴机器人的实验结果。

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