Samsung Electronics Co., Ltd.

Myungjin Eom

Youngo Park

Yumi Sohn

Kwangpyo Choi

Inhak Na

Sungchan Kim

Jongseok Lee

Chanwon Seo

Pilkyu Park

Eunseo Kim

Yehoon Kim

Hyejin Lee

Hyunsoo Choi

Heejeong Lee

Sungjin Kim

Jongyoub Ryu

Seungsoo Kang

Jaewook Shin

Sangha Kim

Hakjung Kim

Jiwan Kim

Junho Rim

Aeran Lim

Soyoon Park

Youngeun Lee

An electronic device recognizing an object is provided. The electronic device includes a plurality of computing units, a memory, and a processor configured to control at least one of the plurality of computing units such that object information about objects obtained by recognizing the objects existing in a space by using a first recognition model, divide the space into a plurality of subset spaces, based on the object information, determine at least one recognition model, based on characteristic information of each of the subset spaces, assign the determined recognition model to one computing unit, based on characteristic information of each of a plurality of computing units and characteristic information of the determined recognition model, and control the plurality of computing units to perform object recognition by using the determined recognition model and the one computing unit in each of the subset spaces.

Electronic device assigning recognition model to computing unit and operating method thereof

An electronic device and a controlling method thereof are provided. An electronic device includes a memory configured to store at least one instruction and a processor configured to execute the at least one instruction and operate as instructed by the at least one instruction. The processor is configured to: obtain a first image; based on receiving a first user command to correct the first image, obtain a second image by correcting the first image; based on the first image and the second image, train a neural network model; and based on receiving a second user command to correct a third image, obtain a fourth image by correcting the third image using the trained neural network model.

Electronic device and controlling method of electronic device

A method of performing object recognition is performed by an electronic device and includes obtaining a spatial map of a space, using a first recognition model, recognizing one or more objects in the space, to obtain first object information of the objects, and dividing the space into a plurality of subset spaces, based on the obtained spatial map and the obtained first object information. The method further includes determining at least one second recognition model to be allocated to each of the plurality of subset spaces into which the space is divided, based on characteristic information of each of the plurality of subset spaces, and using the determined at least one second recognition model allocated to each of the plurality of subset spaces, performing object recognition on each of the plurality of subset spaces, to obtain second object information.

Electronic device for recognizing object and operating method thereof

An electronic apparatus is disclosed. The electronic apparatus includes a sensor, a camera, a memory, a camera and a processor. The memory stores a plurality of artificial intelligence models trained to identify objects and stores information on a map. The first processor provides, to the second processor, area information on an area in which the electronic apparatus is determined, based on sensing data obtained from the sensor, to be located, from among a plurality of areas included in the map. The second processor loads at least one artificial intelligence model of the plurality of artificial intelligence models to the volatile memory based on the area information and identifies an object by inputting the image obtained through the camera to the loaded artificial intelligence model.

Electronic apparatus for object recognition and control method thereof

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.

Decoding apparatus and operating method of the same, and artificial intelligence (AI) up-scaling apparatus and operating method of the same

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.

Method and apparatus for streaming data

Provided is a computer-recordable recording medium having stored thereon a video file including artificial intelligence (AI) encoding data, wherein the AI encoding data includes: image data including encoding information of a low resolution image generated by AI down-scaling a high resolution image; and AI data about AI up-scaling of the low resolution image reconstructed according to the image data, wherein the AI data includes: AI target data indicating whether AI up-scaling is to be applied to at least one frame; and AI supplementary data about up-scaling deep neural network (DNN) information used for AI up-scaling of the at least one frame from among a plurality of pieces of pre-set default DNN configuration information, when AI up-scaling is applied to the at least one frame.

Methods and apparatuses for performing encoding and decoding on image

An electronic device and a method for controlling the electronic device thereof are provided. The electronic device includes a memory storing instructions, and a processor configured to control the electronic device by executing the instructions stored in the memory, and the processor is configured to, based on a user's speech being input, acquire a first sentence in a first language corresponding to the user's speech through a speech recognition model corresponding to a language of the user's speech, acquire a second sentence in a second language corresponding to the first sentence in the first language through a machine translation model trained to translate a plurality of languages into the predefined second language, and acquire a control instruction of the electronic device corresponding to the acquired second sentence or acquire a response to the second sentence through a natural language understanding model trained based on the second language.

Electronic device and method for controlling the electronic device thereof based on determining intent of a user speech in a first language machine translated into a predefined second language

Decoding apparatus and operating method of the same, and artificial intelligence (AI) upscaling apparatus and operating method of the same

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Suwon-si, South Korea

Myungjin Eom