- Patent Title: 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
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Application No.: US17870529Application Date: 2022-07-21
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Publication No.: US12165061B2Publication Date: 2024-12-10
- Inventor: Lok Won Kim
- Applicant: DEEPX CO., LTD.
- Applicant Address: KR Seongnam-si
- Assignee: DEEPX CO., LTD.
- Current Assignee: DEEPX CO., LTD.
- Current Assignee Address: KR Seongnam-si
- Agency: INVENSTONE PATENT, LLC
- Priority: KR10-2019-0001406 20190104,KR10-2019-0002220 20190108
- Main IPC: G06F1/00
- IPC: G06F1/00 ; G06F1/3206 ; G06F1/3287 ; G06F18/214 ; G06N3/08

Abstract:
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.
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