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    METHOD AND APPARATUS FOR CONTROLLING SCALE RESOLUTION IN ELECTRONIC DEVICE
    11.
    发明申请
    METHOD AND APPARATUS FOR CONTROLLING SCALE RESOLUTION IN ELECTRONIC DEVICE 审中-公开
    用于控制电子设备中的尺寸分辨率的方法和装置

    公开(公告)号：US20150177903A1

    公开(公告)日：2015-06-25

    申请号：US14565891

    申请日：2014-12-10

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Soohyung KIM ,  Hyunsoo KIM ,  Sungho SON ,  Sunghyuk SHIN ,  Huncheol OH ,  Jinhong JEONG

    IPC: G06F3/041 ,  G06F3/0354 ,  G06F3/01

    CPC classification number: G06F3/03545 ,  G06F3/04847 ,  G06F3/04855 ,  G06F3/0487 ,  G06F3/0488 ,  G06F3/04883 ,  G06F2203/04806 ,  G06F2203/04807

    Abstract: A method and apparatus that control scale resolution according to various types of information extracted from distinct input means in an electronic device is provided. The method includes presenting information on a display module functionally connected to the electronic device, detecting a first user input related to the presented information, determining scale resolution based at least in part on the first user input, and executing, upon detection of a second user input, a preset function based at least in part on the second user input and the scale resolution.

    Abstract translation: 提供了一种根据从电子设备中的不同输入装置提取的各种信息来控制缩放分辨率的方法和装置。 该方法包括在功能上连接到电子设备的显示模块上呈现信息，检测与所呈现的信息相关的第一用户输入，至少部分地基于第一用户输入确定缩放分辨率，以及在检测到第二用户时执行 输入，至少部分地基于第二用户输入和比例分辨率的预设功能。

    METHOD AND DEVICE FOR CONTROLLING ELECTRONIC DEVICE FOR FEDERATED LEARNING
    12.
    发明申请
    METHOD AND DEVICE FOR CONTROLLING ELECTRONIC DEVICE FOR FEDERATED LEARNING 有权

    公开(公告)号：US20230076024A1

    公开(公告)日：2023-03-09

    申请号：US17986519

    申请日：2022-11-14

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Chunghun BAEK ,  Sungwook KIM ,  Soohyung KIM ,  Dongkyun NAM

    IPC: G06N20/00 ,  H04L9/30 ,  H04L9/08

    Abstract: Embodiments of the disclosure relate to an electronic device and a server for federated learning, and a method of the same. A method of refining a core artificial intelligence (AI) model built in the server includes transmitting, to each of a plurality of electronic devices performing federated learning with the core AI model, data for requesting transmission of first data used for refining the core AI model, receiving first data from at least one of the plurality of electronic devices, identifying an electronic device that has transmitted the first data from among the plurality of electronic devices, transmitting data for requesting transmission of second data to the electronic device that has transmitted the first data among the plurality of electronic devices, receiving second data from the electronic device that has transmitted the first data, and refining the core AI model by using the first data and the second data, wherein the first data includes first differential privacy protection data for protecting private data of each of the plurality of electronic devices, and the second data includes differential privacy modification data used to modify the first differential privacy protection data into second differential privacy protection data.

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