首页> 外国专利> TRAINED MODEL CREATION METHOD FOR PERFORMING SPECIFIC FUNCTION FOR ELECTRONIC DEVICE, TRAINED MODEL FOR PERFORMING SAME FUNCTION, EXCLUSIVE CHIP AND OPERATION METHOD FOR THE SAME, AND ELECTRONIC DEVICE AND SYSTEM USING THE SAME

TRAINED MODEL CREATION METHOD FOR PERFORMING SPECIFIC FUNCTION FOR ELECTRONIC DEVICE, TRAINED MODEL FOR PERFORMING SAME FUNCTION, EXCLUSIVE CHIP AND OPERATION METHOD FOR THE SAME, AND ELECTRONIC DEVICE AND SYSTEM USING THE SAME

机译:用于执行电子设备特定功能的训练模型创建方法、用于执行相同功能的训练模型、用于执行相同功能的专用芯片和操作方法,以及使用相同的电子设备和系统

摘要

A learning model creation method for performing a specific function for an electronic device, according to an embodiment of the present invention, can include the steps of: preparing big data for training an artificial neural network including, in pairs, sensing data received from a random sensing data generation unit for sensing human behaviors and specific function performance determination data for determining whether to perform a specific function of an electronic device with respect to the sensing data; preparing an artificial neural network model, which includes nodes of an input layer through which the sensing data is inputted, nodes of an output layer through which the specific function performance determination data of the electronic device is outputted, and association parameters between the nodes of the input layer and the nodes of the output layer, and calculates inputs of the sensing data for the nodes of the input layer in order to output the specific function performance determination data from the nodes of the output layer; and repeatedly performing a process of inputting the sensing data included in the prepared big data into the nodes of the input layer and outputting the specific function performance determination data that pairs with the sensing data included in the big data from the nodes of the output layer so as to update the association parameters, thereby mechanically training the artificial neural network model.
机译:根据本发明的实施例,用于执行电子设备特定功能的学习模型创建方法,可以包括以下步骤:准备用于训练人工神经网络的大数据,包括成对地从随机传感数据生成单元接收的用于感知人类行为的传感数据和用于确定是否执行电子设备的特定功能的特定功能性能确定数据。传感数据;准备人工神经网络模型,包括输入传感数据的输入层节点、输出电子设备特定功能性能确定数据的输出层节点、输入层节点与输出层节点之间的关联参数, 并计算输入层节点的传感数据输入,以便从输出层的节点输出特定的功能性能确定数据;并重复执行将准备好的大数据中包含的感知数据输入到输入层节点中,并从输出层节点输出与大数据中包含的感知数据配对的特定功能性能确定数据的过程,从而更新关联参数, 从而对人工神经网络模型进行机械训练。

著录项

  • 公开/公告号US20220357792A1;US2022000357792A1;US2022357792A1;US2022357792

    专利类型

  • 公开/公告日2022-11-10

    原文格式PDF

  • 申请/专利权人 DEEPX CO. LTD.;

    申请/专利号US17870529;US202200017870529;US202217870529A;US202217870529

  • 发明设计人

    申请日2022-07-21

  • 分类号G06F1/3287;G06F1/3206;G06K9/62;G06N3/08;

  • 国家

  • 入库时间 2024-06-14 23:43:23

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