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    METHOD AND SYSTEM OF PERFORMING CONVOLUTION IN NEURAL NETWORKS WITH VARIABLE DILATION RATE
    1.
    发明申请
    METHOD AND SYSTEM OF PERFORMING CONVOLUTION IN NEURAL NETWORKS WITH VARIABLE DILATION RATE 审中-公开

    公开(公告)号：US20200218936A1

    公开(公告)日：2020-07-09

    申请号：US16733314

    申请日：2020-01-03

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： DINESH KUMAR YADAV ,  ANKUR DESHWAL ,  SAPTARSI DAS ,  Junwoo JANG ,  Sehwan LEE

    IPC: G06K9/62 ,  G06T1/00 ,  G06N3/08

    Abstract: A method of performing convolution in a neural network with variable dilation rate is provided. The method includes receiving a size of a first kernel and a dilation rate, determining at least one of size of one or more disintegrated kernels based on the size of the first kernel, a baseline architecture of a memory and the dilation rate, determining an address of one or more blocks of an input image based on the dilation rate, and one or more parameters associated with a size of the input image and the memory. Thereafter, the one or more blocks of the input image and the one or more disintegrated kernels are fetched from the memory, and an output image is obtained based on convolution of each of the one or more disintegrated kernels and the one or more blocks of the input image.

    METHOD AND SYSTEM OF PERFORMING CONVOLUTION IN NEURAL NETWORKS WITH VARIABLE DILATION RATE
    2.
    发明申请
    METHOD AND SYSTEM OF PERFORMING CONVOLUTION IN NEURAL NETWORKS WITH VARIABLE DILATION RATE 有权

    公开(公告)号：US20220374651A1

    公开(公告)日：2022-11-24

    申请号：US17851704

    申请日：2022-06-28

    Applicant: Samsung Electronics Co., Ltd.

    Inventor： DINESH KUMAR YADAV ,  ANKUR DESHWAL ,  SAPTARSI DAS ,  Junwoo JANG ,  Sehwan LEE

    IPC: G06K9/62 ,  G06N3/08 ,  G06T1/00

    Abstract: A method of performing convolution in a neural network with variable dilation rate is provided. The method includes receiving a size of a first kernel and a dilation rate, determining at least one of size of one or more disintegrated kernels based on the size of the first kernel, a baseline architecture of a memory and the dilation rate, determining an address of one or more blocks of an input image based on the dilation rate, and one or more parameters associated with a size of the input image and the memory. Thereafter, the one or more blocks of the input image and the one or more disintegrated kernels are fetched from the memory, and an output image is obtained based on convolution of each of the one or more disintegrated kernels and the one or more blocks of the input image.

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