Samsung Electronics Co., Ltd.

Amogreentech Co., Ltd.

Jaehwan Kim

Youngo Park

Kwangpyo Choi

Jongseok Lee

Minseok Choi

Sunyoung Jeon

Quockhanh Dinh

Chaeeun Lee

Chan Kim

Seunghoon Lee

Heechul Yang

Junghun Kim

Sangmi Park

Jisup Lee

Inyong Seo

Byunggwang Jo

Sangchul Suh

Cheolhyeon Kim

Yongjoon Jeon

Minsoo Kim

Min-Soo Kim

Dongwoo Kim

Jin Sung Kim

Bokun Choi

Jihyun Kim

Jinwoo Lee

Taehoon Kim

Seong-soo Lee

Young-hwan Kim

Jongmu Choi

Shinjun Lee

Wonsuk Chung

Dohoon Kim

Ji-Woo Lee

Yongseok Park

Sanghyup Lee

Sunyong Kim

Jinman Kim

Jae-Hyon Kim

Sunghyun Park

Chulhyung Yang

Changwon Kim

Joonhyuk Kang

Pilkyu Park

Myung-Ho Kim

Oleksandr Baiev

Youngho Rhee

Seung Woo Park

Jongwon Seo

Ki-Man Kim

Ofir Engolz

Yungil Kim

Soonyong Cho

Yonghak Kim

Youngtae Jeong

Amir Dror

Kyungsoo Hong

Byungmoo Kim

Junsu Jeon

Dongeup Ham

Minseo Kang

Sujeong Lim

An-Ki Cho

Keumju Jang

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 to obtain image data generated through first encoding on a first image; obtain a second image corresponding to the first image by performing first decoding on the image data; perform pre-processing of changing a resolution of the second image, according to a pre-determined output resolution; and obtain a fourth image having the pre-determined output resolution by applying AI up-scaling based on an up-scaling deep neural network (DNN) to a third image obtained as a result of the pre-processing.

Apparatus and method for performing artificial intelligence encoding and artificial intelligence decoding on image by using pre-processing

Provided is an electronic device configured to participate in video conference by using artificial intelligence (AI), the electronic device including a display and a processor configured to execute one or more instructions. The processor configured to obtain, from a server, image data generated by first encoding first image related to another electronic device participating in video conference, and AI data related to AI downscaling from original image to first image, obtain second image corresponding to first image by performing first decoding on image data, determine whether to perform AI upscaling on second image, based on importance of the other electronic device, based on determining to perform AI upscaling, obtain third image by performing AI upscaling on second image through an upscaling deep neural network and provide third image to display, and based on determining not to perform AI upscaling, provide second image to display.

Method and apparatus for artificial intelligence downscaling and upscaling during video conference

Provided is an electronic apparatus configured to provide an image based on artificial intelligence (AI), the electronic apparatus including a processor configured to execute one or more instructions stored in the electronic apparatus to obtain a first image by AI-downscaling an original image by a downscaling neural network, obtain first image data by encoding the first image, based on a display apparatus not supporting an AI upscaling function, obtain a second image by decoding the first image data, obtain a third image by AI-upscaling the second image by an upscaling neural network, and provide, to the display apparatus, second image data obtained by encoding the third image.

Image providing method and apparatus using artificial intelligence, and display method and apparatus using artificial intelligence

An electronic apparatus includes: a display; and a processor configured to: obtain a first image, identify an application used to obtain the first image, select neural network setting information corresponding to the identified application from among a plurality of pieces of neural network setting information, obtain a second image by artificial intelligence (AI)-upscaling the first image by using an upscaling neural network to which the selected neural network setting information is applied, and output the obtained second image via the display.

Electronic apparatus and method for reproducing image based on artificial intelligence according to application

Provided is a method of adaptively performing artificial intelligence (AI) downscaling on an image during a video telephone call of a user terminal. The method includes obtaining, from an opposite user terminal, AI upscaling support information of the opposite user terminal that is a target of a video telephone call, determining whether the user terminal is to perform AI downscaling on an original image, based on the AI upscaling support information, based on determining that the user terminal is to perform AI downscaling on the original image, obtaining a first image by AI downscaling the original image using a downscaling deep neural network (DNN), generating image data by performing first encoding on the first image, and transmitting AI data including information related to the AI downscaling and the image data.

Method and apparatus for adaptive artificial intelligence downscaling for upscaling during video telephone call

An apparatus for performing artificial intelligence (AI) encoding on an image includes: a memory storing one or more instructions; and a processor configured to execute the one or more instructions stored in the memory to: determine a resolution of an original image; when the resolution of the original image is higher than a predetermined value, obtain a first image by performing AI downscaling on the original image via a downscaling deep neural network (DNN); when the resolution of the original image is lower than or equal to the predetermined value, obtain a first image by performing AI one-to-one preprocessing on the original image via a one-to-one preprocessing DNN for upscaling; generate image data by performing first encoding on the first image; and transmit the image data and AI data including information related to the AI downscaling or information related to the AI one-to-one preprocessing.

Method and apparatus for performing artificial intelligence encoding and artificial intelligence decoding

An artificial intelligence (AI) decoding method including obtaining image data generated from performing first encoding on a first image and AI data related to AI down-scaling of at least one original image related to the first image; obtaining a second image corresponding to the first image by performing first decoding on the image data; obtaining, based on the AI data, deep neural network (DNN) setting information for performing AI up-scaling of the second image; and generating a third image by performing the AI up-scaling on the second image via an up-scaling DNN operating according to the obtained DNN setting information. The DNN setting information is DNN information updated for performing the AI up-scaling of at least one second image via joint training of the up-scaling DNN and a down-scaling DNN used for the AI down-scaling.

Apparatus and method for performing artificial intelligence (AI) encoding and AI decoding on image

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 downscaled from an original image by using first parameters of a first filter kernel included in a first deep neural network (DNN), reconstruct a second image corresponding to the first image, based on the obtained image data, and obtain a third image that is upscaled from the reconstructed second image, by performing an operation between the reconstructed second image and second parameters of a second filter kernel included in a second DNN corresponding to the first DNN. Each of the second parameters is represented by a product of a scale factor and one among integer values, and each of the integer values is 0 or &#xb1;2, where n is an integer.

Artificial intelligence (AI) encoding device and operating method thereof and AI decoding device and operating method thereof

Disclosed are an electronic apparatus and a method of controlling the same. The electronic apparatus includes a camera, a display, a memory, and a processor configured to execute at least one instruction to: detect a plurality of fingers in a plurality of first image frames obtained through the camera and, in response to an identification that a pose of the plurality of detected fingers corresponds to a trigger pose, enter a character input mode, detect a first motion of a finger among the plurality of fingers in a plurality of second image frames obtained through in the character input mode, identify a key corresponding to the first motion, from among a plurality of keys mapped to the finger, based on a position of the finger by the first motion and a reference point set to the finger, and control the display to display information corresponding to the identified key.

Electronic apparatus for providing a virtual keyboard and controlling method thereof

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.

Apparatuses and methods for performing artificial intelligence encoding and artificial intelligence decoding on image

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.

Methods and apparatuses for performing artificial intelligence encoding and artificial intelligence decoding on image

A method of providing information about an object in a refrigerator is provided. The method includes: obtaining, using a camera, an image of a plurality of objects stored in the refrigerator; displaying the image on a display of the refrigerator; receiving a first user input indicating a first object from among the plurality of objects included in the image; and displaying a substitute image of the first object on the display based on the first user input.

Method and system for providing information about objects in refrigerator

A method of designing a layout of a semiconductor device includes determining from among a plurality of integrated circuit (IC) blocks in the semiconductor device a selection IC block for which a layout is to be changed, changing an spacing interval at which fin structures included in the selection IC block are spaced apart from each other in a first direction from a first spacing interval to a second spacing interval, and determining in the selection IC block locations of source/drain regions connected to the fin structures spaced apart from each other in the first direction at the second spacing interval.

Methods of designing layouts of semiconductor devices

Growing community of inventors

Suwon-si, South Korea

Jaehwan Kim