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    METHOD AND DEVICE WITH VIDEO CONVERSION
    2.
    发明公开
    METHOD AND DEVICE WITH VIDEO CONVERSION 审中-公开

    公开(公告)号：US20240187614A1

    公开(公告)日：2024-06-06

    申请号：US18350233

    申请日：2023-07-11

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Hyoa KANG ,  Hee Min CHOI

    IPC: H04N19/184 ,  G06V10/764 ,  G06V10/82

    CPC classification number: H04N19/184 ,  G06V10/764 ,  G06V10/82

    Abstract: A processor-implemented method includes: initializing a neural network model with arbitrary values using a random seed; training the neural network model based on the arbitrary values; determining a number of coats and respective densities of the coats; learning respective scores of parameters of the neural network model based on the number of coats and the respective densities of the coats; determining mask information for determining the parameters of the neural network model to be comprised in each of the coats based on the scores; and generating a bitstream based on the number of coats, the respective densities of the coats, the mask information, and the random seed.

    METHOD AND APPARATUS WITH NEURAL NETWORK TRAINING
    3.
    发明申请
    METHOD AND APPARATUS WITH NEURAL NETWORK TRAINING 有权

    公开(公告)号：US20220237890A1

    公开(公告)日：2022-07-28

    申请号：US17550184

    申请日：2021-12-14

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： Hee Min CHOI ,  Hyoa KANG

    IPC: G06V10/762 ,  G06V20/58 ,  G06N3/04

    Abstract: A processor-implemented method with neural network training includes: determining first backbone feature data corresponding to each input data by applying, to a first neural network model, two or more sets of the input data of the same scene, respectively; determining second backbone feature data corresponding to each input data by applying, to a second neural network model, the two or more sets of the input data, respectively; determining projection-based first embedded data and dropout-based first view data from the first backbone feature data; and determining projection-based second embedded data and dropout-based second view data from the second backbone feature data; and training either one or both of the first neural network model and the second neural network model based on a loss determined based on a combination of any two or more of the first embedded data, the first view data, the second embedded data, the second view data, and an embedded data clustering result.

    METHOD AND APPARATUS FOR DETERMINING ABNORMAL OBJECT
    8.
    发明申请
    METHOD AND APPARATUS FOR DETERMINING ABNORMAL OBJECT 审中-公开

    公开(公告)号：US20180150701A1

    公开(公告)日：2018-05-31

    申请号：US15583339

    申请日：2017-05-01

    Applicant: SAMSUNG ELECTRONICS CO., LTD.

    Inventor： Hyoa KANG ,  Changhyun KIM

    IPC: G06K9/00 ,  G06K9/62 ,  G06K9/78 ,  G06K9/46 ,  G06N3/08

    Abstract: Disclosed is a method and apparatus for determining an abnormal object, the method including selecting a candidate object from target objects extracted from a two-dimensional (2D) image of a front view captured from a host vehicle, generating a three-dimensional (3D) model of the candidate object, determining, based on the 3D model, whether the candidate object corresponds to an abnormal object that interferes with driving of the host vehicle, and outputting the abnormal object, in response to the candidate object corresponding to the abnormal object.

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