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Verification of the Effectiveness of the Online Tuning System for Unknown Person in the Awaking Behavior Detection System

机译:在觉醒行为检测系统中验证未知人在线调整系统的有效性

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We have developed an awaking behavior detection system using a neural network (abbreviated as NN). However, the detection ability of unknown people is not sufficient with compared to that of learned people. In this research, to improve the detection ability of unknown people, we apply an online tuning system using a continuous learning of the NN for the detection system. In the online tuning system, only a few additional data of a new objective person are used for the continuous learning, where the weights of the NN converged in the initial learning are used as the initial weights for the continuous learning. In this paper, to verify an ability of the online tuning system, we compare detection ability of the converged initial learning with that of the converged online tuning.
机译:我们已经开发了使用神经网络(缩写为NN)的唤醒行为检测系统。但是,与学习者相比,未知者的检测能力不足。在这项研究中,为提高未知人员的检测能力,我们将在线学习系统应用于网络,该系统使用对神经网络的连续学习作为检测系统。在在线调整系统中,仅新目标对象的一些其他数据用于连续学习,其中在初始学习中收敛的NN的权重用作连续学习的初始权重。在本文中,为了验证在线调整系统的功能,我们将融合的初始学习与融合的在线调整的检测能力进行了比较。

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