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    METHOD AND APPARATUS FOR MODELING BASED ON PARTICLES FOR EFFICIENT CONSTRAINTS PROCESSING
    21.
    发明申请
    METHOD AND APPARATUS FOR MODELING BASED ON PARTICLES FOR EFFICIENT CONSTRAINTS PROCESSING 审中-公开
    基于有效约束处理颗粒的建模方法与装置

    公开(公告)号：US20170024498A1

    公开(公告)日：2017-01-26

    申请号：US15187135

    申请日：2016-06-20

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Nahyup KANG ,  Jiyeon KIM ,  Donghoon SAGONG ,  Hyong Euk LEE ,  Hwiryong JUNG

    IPC: G06F17/50 ,  G06F7/02

    Abstract: A modeling method based on particles, the method including generating coarse particles by down-sampling target particles corresponding to at least a portion of a target object, calculating a correcting value enabling the coarse particles to satisfy constraints of the target object based on physical attributes of the target particles, applying the correcting value to the target particles, and redefining the target particles in response to the target particles to which the correcting value is applied satisfying the constraints.

    Abstract translation: 一种基于粒子的建模方法，该方法包括：通过对与目标对象的至少一部分相对应的目标粒子进行下采样来生成粗粒子;计算使得粗粒子能够基于物理属性的物理属性来满足目标对象的约束的校正值 目标颗粒，将校正值应用于目标颗粒，并且响应于满足约束条件的施加了校正值的目标颗粒重新定义目标颗粒。

    METHOD AND APPARATUS WITH POSE ESTIMATION
    23.
    发明申请
    METHOD AND APPARATUS WITH POSE ESTIMATION 有权

    公开(公告)号：US20230035458A1

    公开(公告)日：2023-02-02

    申请号：US17584682

    申请日：2022-01-26

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Hojin JU ,  Yun-Tae KIM ,  Donghoon SAGONG ,  Jaehwan PI

    IPC: G06T7/70 ,  G06T7/246 ,  G06T19/00 ,  G02B27/01

    Abstract: A processor-implemented method with pose estimation includes: tracking a position of a feature point extracted from image information comprising a plurality of image frames, the image information being received from an image sensor; predicting a current state variable of an estimation model for determining a pose of an electronic device, based on motion information received from a motion sensor; determining noise due to an uncertainty of the estimation model based on a residual between a first position of the feature point extracted from the image frames and a second position of the feature point predicted based on the current state variable; updating the current state variable based on the current state variable, the tracked position of the feature point, and the noise; and determining the pose of the electronic device based on the updated current state variable.

    NEURAL NETWORK RECOGNTION AND TRAINING METHOD AND APPARATUS
    24.
    发明申请
    NEURAL NETWORK RECOGNTION AND TRAINING METHOD AND APPARATUS 审中-公开

    公开(公告)号：US20190102678A1

    公开(公告)日：2019-04-04

    申请号：US15946800

    申请日：2018-04-06

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Hyun Sung CHANG ,  Donghoon SAGONG ,  Minjung SON

    IPC: G06N3/08 ,  G06N3/04 ,  G06K9/62 ,  G06F17/18

    Abstract: Disclosed is a recognition and training method and apparatus. The apparatus may include a processor configured to input data to a neural network, determine corresponding to a multiclass output a mapping function of a first class and a mapping function of a second class, acquire a result of a loss function including a first probability component that changes correspondingly to a function value of the mapping function of the first class and a second probability component that changes contrastingly to a function value of the mapping function of the second class, determine a gradient of loss corresponding to the input data based on the result of the loss function, update a parameter of the neural network based on the determined gradient of loss for generating a trained neural network based on the updated parameter. The apparatus may input other data to the trained neural network, and indicate a recognition result.

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