公开(公告)号：US20220067419A1

公开(公告)日：2022-03-03

申请号：US17177702

申请日：2021-02-17

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： JAEHYOUNG YOO ,  CHANGYONG SON ,  DONGWOOK LEE ,  JAEJOON HAN ,  CHANG KYU CHOI

IPC: G06K9/46 ,  G06N3/04 ,  G06N3/08 ,  H04N5/232

Abstract: A method and apparatus for processing an image based on partial images. The method includes extracting a feature of a current partial processing region of an input image frame by inputting pixel data of the current partial processing region into a convolutional neural network (CNN), updating a hidden state of a recurrent neural network (RNN) for a context between the current partial processing region and at least one previous partial processing region by inputting the extracted feature into the RNN, and generating an image processing result for the input image frame based on the updated hidden state.

公开(公告)号：US20230245267A1

公开(公告)日：2023-08-03

申请号：US17981961

申请日：2022-11-07

Applicant: Samsung Electronics Co., Ltd.

Inventor： SANGIL JUNG ,  SEUNGIN PARK ,  JAEHYOUNG YOO ,  SOLAE LEE ,  BYUNG IN YOO ,  HANA LEE

IPC: G06T3/40 ,  G06T5/50

CPC classification number: G06T3/4007 ,  G06T5/50 ,  G06T2207/20228 ,  G06T2207/20076

Abstract: An apparatus and method with image processing for sparse dual-pixel image data are included. In one general aspect, an apparatus includes a processor configured to generate a first interpolated image by performing interpolation on a first image and generate a second interpolated image by performing interpolation on a second image, wherein the first image and the second image comprise pixel values obtained by dual-pixels of an image sensor, and generate a disparity map based on the first interpolated image and the second interpolated image.

公开(公告)号：US20210192315A1

公开(公告)日：2021-06-24

申请号：US17071063

申请日：2020-10-15

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： JINWOO SON ,  CHANGYONG SON ,  JAEHYOUNG YOO ,  SEOHYUNG LEE ,  SANGIL JUNG ,  CHANGIN CHOI

IPC: G06N3/04 ,  G06N3/08

Abstract: A processor-implemented neural network method includes: generating a first output line of an output feature map by performing a convolution operation between a first input line group of an input feature map and weight kernels; generating a first output of an operation block including the convolution operation based on the first output line; and storing the first output in a memory in which the input feature map is stored by overwriting the first output to a memory space of the memory.