公开(公告)号：US20250139743A1

公开(公告)日：2025-05-01

申请号：US18920308

申请日：2024-10-18

Applicant: Samsung Electronics Co., Ltd.

Inventor： Insoo KIM ,  Geonseok SEO ,  Jae Seok CHOI ,  Hyong Euk LEE

IPC: G06T5/60 ,  G06T5/20 ,  G06T5/70 ,  G06T7/215 ,  G06T7/246 ,  G06V10/762 ,  G06V10/764 ,  G06V10/77 ,  G06V10/82 ,  G06V20/70

Abstract: A method and device for image enhancement based on blur segmentation are provided. The method of image enhancement includes: generating a blur segmentation map including indications of blur characteristics of respective pixels of a blur image, wherein the blur characteristics are in predetermined blur characteristic categories, and wherein the generating is performed by classifying the blur characteristic of each pixel of the blur image into one of the predetermined blur characteristic categories; converting the blur segmentation map into an image residual error corresponding to a blur component of the blur image; and generating the deblurred image based on the blur image and the image residual error.

公开(公告)号：US20220156888A1

公开(公告)日：2022-05-19

申请号：US17318287

申请日：2021-05-12

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Insoo KIM ,  Seungju HAN ,  Seong-jin PARK ,  Jiwon BAEK ,  Jaejoon HAN

IPC: G06T5/00 ,  G06N3/04 ,  G06N3/08 ,  G06T3/40

Abstract: An image recognition method includes: receiving an input image of a first quality; extracting an input feature of a second quality of the input image from the input image by inputting the input image to an encoding model in an image recognizing model; and generating a recognition result for the input image based on the input feature.

公开(公告)号：US20240054606A1

公开(公告)日：2024-02-15

申请号：US18337774

申请日：2023-06-20

Applicant: Samsung Electronics Co., Ltd.

Inventor： Geonseok SEO ,  Sehwan KI ,  Jae Seok CHOI ,  Insoo KIM ,  Hyong Euk LEE

IPC: G06T5/00 ,  G06T5/50

CPC classification number: G06T5/001 ,  G06T5/50 ,  G06T2207/20084

Abstract: A processor-implemented method includes: obtaining a plurality of image frames acquired for a scene within a predetermined time; determining loss values respectively corresponding to the plurality of image frames; determining a reference frame among the plurality of image frames based on the loss values; and generating a final image of the scene based on the reference frame.

公开(公告)号：US20210181306A1

公开(公告)日：2021-06-17

申请号：US17019672

申请日：2020-09-14

Applicant: Samsung Electronics Co., Ltd.

Inventor： Insoo KIM ,  Seungju HAN ,  Jaejoon HAN

IPC: G01S7/41 ,  G06F21/44

Abstract: A processor-implemented radar data recognition method includes: generating a plurality of pieces of input data, with respectively different dimension configurations, based on radar data of an object; and outputting a recognition result of the object based on the generated plurality of pieces of input data using a recognition model.

公开(公告)号：US20230366982A1

公开(公告)日：2023-11-16

申请号：US18354179

申请日：2023-07-18

Applicant: Samsung Electronics Co., Ltd.

Inventor： Insoo KIM ,  Seungju HAN ,  Jaejoon HAN

IPC: G01S7/41 ,  G06F21/44

CPC classification number: G01S7/412 ,  G06F21/44

Abstract: A processor-implemented radar data recognition method including generating a plurality of pieces of input data, with respectively different dimension configurations, based on radar data of an object; and outputting a recognition result of the object based on the generated plurality of pieces of input data using a recognition model.

公开(公告)号：US20220058377A1

公开(公告)日：2022-02-24

申请号：US17208048

申请日：2021-03-22

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Jiwon BAEK ,  Seong-Jin PARK ,  Seungju HAN ,  Insoo KIM ,  Jaejoon HAN

IPC: G06K9/00 ,  G06T9/00 ,  G06K9/62 ,  G06T7/73 ,  G06T3/60 ,  G06T3/40 ,  G06N3/04 ,  G06N3/08

Abstract: A processor-implemented facial image generating method includes: determining a first feature vector associated with a pose and a second feature vector associated with an identity by encoding an input image including a face; determining a flipped first feature vector by flipping the first feature vector with respect to an axis in a corresponding space; determining an assistant feature vector based on the flipped first feature vector and rotation information corresponding to the input image; determining a final feature vector based on the first feature vector and the assistant feature vector; and generating an output image including a rotated face by decoding the final feature vector and the second feature vector based on the rotation information.

公开(公告)号：US20250103209A1

公开(公告)日：2025-03-27

申请号：US18891579

申请日：2024-09-20

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Insoo KIM

IPC: G06F3/06

Abstract: A memory system includes a memory device, and a memory controller connected to the memory device. The memory controller is configured to analyze a pattern of the suspend schedule command a plurality of times to obtain a plurality of analysis results, select an operating mode from among a plurality of operating modes based on the plurality of analysis results, determine a suspend schedule based on the operating mode, and perform a memory operation on the memory device based on the suspend schedule. The plurality of operating modes including a latency mode and a throughput mode. The memory operation including at least one of a read operation or a write operation.

公开(公告)号：US20250045371A1

公开(公告)日：2025-02-06

申请号：US18920277

申请日：2024-10-18

Applicant: Samsung Electronics Co., Ltd.

Inventor： Jiwon BAEK ,  Seungju HAN ,  Kikyung KIM ,  Insoo KIM ,  Jaejoon HAN

IPC: G06F21/32 ,  G06V10/74 ,  G06V10/77 ,  G06V10/82 ,  G06V40/16 ,  G06V40/40

Abstract: A method with access authority management includes: receiving an input image comprising a region of at least one portion of a body of a user; determining whether the user corresponds to multiple users or a single user using the region of the at least one portion of the body; performing a verification for the user based on a face region in the input image, in response to the determination that the user is the single user; determining whether the input image is a real image or a spoofed image based on whether the verification is successful; and allowing an access authority to a system to the user, in response to the determination that the input image is the real image.

公开(公告)号：US20230037263A1

公开(公告)日：2023-02-02

申请号：US17671747

申请日：2022-02-15

Applicant: Samsung Electronics Co., Ltd.

Inventor： Jiwon BAEK ,  Seungju HAN ,  Kikyung KIM ,  Insoo KIM ,  Jaejoon HAN

IPC: G06F21/32 ,  G06V40/16 ,  G06V40/40 ,  G06V10/74 ,  G06V10/77 ,  G06V10/82

Abstract: A method with access authority management includes: receiving an input image comprising a region of at least one portion of a body of a user; determining whether the user corresponds to multiple users or a single user using the region of the at least one portion of the body; performing a verification for the user based on a face region in the input image, in response to the determination that the user is the single user; determining whether the input image is a real image or a spoofed image based on whether the verification is successful; and allowing an access authority to a system to the user, in response to the determination that the input image is the real image.

公开(公告)号：US20210241098A1

公开(公告)日：2021-08-05

申请号：US17119381

申请日：2020-12-11

Applicant: SAMSUNG ELECTRONICS CO., LTD. ,  Korea Advanced Institute of Science and Technology

Inventor： Seong-Jin PARK ,  Sung Ju HWANG ,  Seungju HAN ,  Insoo KIM ,  Jiwon BAEK ,  Jaejoon HAN

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

Abstract: A processor-implemented neural network method includes: extracting, by a feature extractor of a neural network, a plurality of training feature vectors corresponding to a plurality of training class data of each of a plurality of classes including a first class and a second class; determining, by a feature sample generator of the neural network, an additional feature vector of the second class based on a mean vector and a variation vector of the plurality of training feature vectors of each of the first class and the second class; and training a class vector of the second class included in a classifier of the neural network based on the additional feature vector and the plurality of training feature vectors of the second class.