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公开(公告)号：US11170472B2
公开(公告)日：2021-11-09
申请号：US17080501
申请日：2020-10-26
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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公开(公告)号：US11138691B2
公开(公告)日：2021-10-05
申请号：US17080543
申请日：2020-10-26
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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公开(公告)号：US11107190B2
公开(公告)日：2021-08-31
申请号：US17098907
申请日：2020-11-16
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Kwangpyo Choi , Yumi Sohn , Sungchan Kim , Myungjin Eom
Abstract: Provided is a decoding apparatus including: a communication interface configured to receive AI encoding data generated as a result of artificial intelligence (AI) down-scaling and first encoding of an original image; a processor configured to divide the AI encoding data into image data and AI data; and an input/output (I/O) device, wherein the processor is further configured to: obtain a second image by performing first decoding on a first image obtained by performing AI down-scaling on the original image, based on the image data; and control the I/O device to transmit the second image and the AI data to an external apparatus. In some embodiments, the external apparatus performs an AI upscaling of the second image using the AI data, and displays the resulting third image.
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Patent Agency Ranking
公开(公告)号：US20210073946A1
公开(公告)日：2021-03-11
申请号：US17087186
申请日：2020-11-02
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo PARK , Kwangpyo Choi , Yumi Sohn , Sungchan Kim , Myungjin Eom
Abstract: Provided is a decoding apparatus including: a communication interface configured to receive AI encoding data generated as a result of artificial intelligence (AI) down-scaling and first encoding of an original image; a processor configured to divide the AI encoding data into image data and AI data; and an input/output (I/O) device, wherein the processor is further configured to: obtain a second image by performing first decoding on a first image obtained by performing AI down-scaling on the original image, based on the image data; and control the I/O device to transmit the second image and the AI data to an external apparatus. In some embodiments, the external apparatus performs an AI upscaling of the second image using the AI data, and displays the resulting third image.
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公开(公告)号：US20210056666A1
公开(公告)日：2021-02-25
申请号：US17080543
申请日：2020-10-26
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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公开(公告)号：US10825205B2
公开(公告)日：2020-11-03
申请号：US16793605
申请日：2020-02-18
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehwan Kim , Jongseok Lee , Sunyoung Jeon , Kwangpyo Choi , Minseok Choi , Quockhanh Dinh , Youngo Park
Abstract: Provided is an artificial intelligence (AI) decoding apparatus includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory, the processor is configured to: obtain AI data related to AI down-scaling an original image to a first image; obtain image data corresponding to an encoding result on the first image; obtain a second image corresponding to the first image by performing a decoding on the image data; obtain deep neural network (DNN) setting information among a plurality of DNN setting information from the AI data; and obtain, by an up-scaling DNN, a third image by performing the AI up-scaling on the second image, the up-scaling DNN being configured with the obtained DNN setting information, wherein the plurality of DNN setting information comprises a parameter used in the up-scaling DNN, the parameter being obtained through joint training of the up-scaling DNN and a down-scaling DNN, and wherein the down-scaling DNN is used to obtain the first image from the original image.
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公开(公告)号：US10817989B2
公开(公告)日：2020-10-27
申请号：US16831521
申请日：2020-03-26
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehwan Kim , Jongseok Lee , Sunyoung Jeon , Kwangpyo Choi , Minseok Choi , Quockhanh Dinh , Youngo Park
Abstract: An artificial intelligence (AI) decoding apparatus includes a memory storing one or more instructions, and a processor configured to execute the stored one or more instructions, to obtain image data corresponding to a first image that is encoded, obtain a second image corresponding to the first image by decoding the obtained image data, determine whether to perform AI up-scaling of the obtained second image, based on the AI up-scaling of the obtained second image being determined to be performed, obtain a third image by performing the AI up-scaling of the obtained second image through an up-scaling deep neural network (DNN), and output the obtained third image, and based on the AI up-scaling of the obtained second image being determined to be not performed, output the obtained second image.
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公开(公告)号：US10817986B2
公开(公告)日：2020-10-27
申请号：US16659061
申请日：2019-10-21
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Youngo Park , Yumi Sohn , Myungjin Eom , Kwangpyo Choi
Abstract: A terminal for receiving streaming data may receive information of a plurality of different quality versions of an image content; request, based on the information, a server for a version of the image content from among the plurality of different quality versions of the image content; when the requested version of the image content and artificial intelligence (AI) data corresponding to the requested version of the image content are received, determines whether to perform AI upscaling on the received version of the image content, based on the AI data; and based on a result of the determining whether to perform AI upscaling, performs AI upscaling on the received version of the image content through a upscaling deep neural network (DNN) that is trained jointly with a downscaling DNN of the server.
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