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公开(公告)号：US20200005081A1
公开(公告)日：2020-01-02
申请号：US16565154
申请日：2019-09-09
Applicant: LG ELECTRONICS INC.
Inventor： Heeyeon NAH , Daesung KIM , Jaewoong YUN
IPC: G06K9/62 , G06F3/0488 , G06K9/00 , G06K9/03
Abstract: Provided is a method for recognizing handwritten characters in a terminal through federated learning. In the method, a first common prediction model for recognizing text from handwritten characters input from a user is applied, the handwritten characters are received from the user, feature values are extracted from an image including the handwritten characters, the feature values are input to the first common prediction mode, first text information is determined from an output of the first common prediction model, the first text information and a second text information received from the user for error correction of the first text information are cached, and the first common prediction model is learned using the image including the handwritten characters, the first text information, and the second text information. In this way, the terminal can determine the text from the handwritten characters input by the user, and can learn the first common prediction model through a feedback operation of the user.
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2.发明申请公开(公告)号：US20200027019A1
公开(公告)日：2020-01-23
申请号：US16584505
申请日：2019-09-26
Applicant: LG ELECTRONICS INC.
Inventor： Injung YANG , Seongrae KIM , Sangyeob YOON , Jaewoong YUN
Abstract: A method for training a model for creating POI data on a terminal through federated learning is disclosed. The method for training a model for creating POI data on a terminal through federated learning includes: receiving an SMS (short message service) message for notifying that a user of the terminal has made a payment; feeding the SMS message into a store information extraction model and acquiring store information from an output of the store information extraction model; acquiring current location information of the terminal; caching POI (point of interest) data, which is the location information labeled with the stored information; and training a first common prediction model using the POI data, wherein the first common prediction model is received through a server, and the SMS message contains text information indicating the business name of the store where the user has made the payment. The terminal of the present disclosure can be associated with artificial intelligence modules, drones (unmanned aerial vehicles (UAVs)), robots, augmented reality (AR) devices, virtual reality (VR) devices, devices related to 5G service, etc.
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公开(公告)号：US20200005071A1
公开(公告)日：2020-01-02
申请号：US16565417
申请日：2019-09-09
Applicant: LG ELECTRONICS INC.
Inventor： Daesung KIM , Heeyeon NAH , Jaewoong YUN
Abstract: Provided is a method of recognizing a business card of a terminal through federated learning, including receiving an image of the business card; extracting a feature value from the image including text related to a field of an address book set in the terminal; inputting the feature value into a first common prediction model and determining first text information from an output of the first common prediction model; analyzing a pattern of the first text information and inputting the first text information into the field; caching the first text information and second text information received for error correction of the first text information from a user; and training the first common prediction model using the image, the first text information, and the second text information, whereby each terminal may train and share the first common prediction model.
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