Samsung Electronics Co., Ltd.

Yehoon Kim

Chanwon Seo

Sojung Yun

Myungjin Eom

Inhak Na

Eunseo Kim

Lei Zhang

Junik Jang

Yongsung Kim

Hyunsoo Choi

Hyungmin Lee

Juyoung Lee

Younguk Kim

Hyosang Kim

Hyunhan Kim

Kyungsu Kim

Dongwan Lee

Ohjoon Kwon

A method and electronic device for recognizing a product are provided. The method includes obtaining first feature information and second feature information from an image related to a product, obtaining fusion feature information based on the first feature information and the second feature information by using a main encoder model that reflects a correlation between feature information of different modalities, matching the fusion feature information against a database of the product, and providing information about the product, based on a result of the matching.

Method and electronic device for recognizing product

An example method for controlling an electronic device includes detecting at least one user and acquiring user information of the detected at least one user; determining a user mode based on the acquired user information; determining a service to be provided to the detected at least one user, by inputting the user information and the determined user mode as input data to a model learned by an artificial intelligence algorithm; and providing the determined service corresponding to the user mode. A method for providing the service by the electronic device may at least partially use an artificial intelligence model learned according to at least one of machine learning, neural network, and deep learning algorithms.

Electronic device and method for controlling same

Provided are an artificial intelligence (AI) system that mimics cognitive functions, such as cognition and judgment, of the human brain using a machine learning algorithm such as deep learning and applications thereof. More particularly, provided is a device including a memory storing least one program and a first video, a display, and at least one processor configured to display the first video on at least one portion of the display by executing the at least one program, wherein the at least one program includes instructions for: comparing an aspect ratio of the first video with an aspect ratio of an area in which the first video is to be displayed, generating a second video corresponding to the aspect ratio of the area by using the first video when the aspect ratio of the first video is different from the aspect ratio of the area, and displaying the second video in the area, wherein the generating of the second video is performed by inputting at least one frame of the first video to an AI neural network.

Video playback device and control method thereof

Provided are a speech recognition device and method. The speech recognition device includes a microphone and a processor configured to receive a voice signal through the microphone, generate voice characteristic data by analyzing the voice signal by using a data recognition model based on a neural network, determine whether the voice signal is voice uttered from a user or voice output from an external device based on the voice characteristic data, and when the voice signal is determined as the voice uttered from the user, determine the voice signal as a voice command of the user and perform an operation corresponding to the voice command. The present disclosure also relates to an artificial intelligence (AI) system utilizing a machine learning algorithm such as deep learning, and applications thereof.

Speech recognition device and method

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

An electronic device and a method for controlling the same are disclosed. The method for controlling an electronic device according to the present disclosure comprises the steps of: detecting at least one user and acquiring user information of the detected at least one user; determining a user mode on the basis of the acquired user information; determining a service to be provided to the detected at least one user, by inputting the user information and the determined user mode as input data to a model learned by an artificial intelligence algorithm; and providing the determined service corresponding to the user mode. A method for providing the service by the electronic device may at least partially use an artificial intelligence model learned according to at least one of machine learning, neural network, and deep learning algorithms.

Provided is a method, performed by an electronic device, of recognizing an object included in an image, the method including: extracting first object information from a first object included in a first image, obtaining a learning model for generating an image including a second object from the first object information, generating a second image including the second object by inputting the first object information to the learning model, comparing the first image with the second image, and recognizing the first object as the second object in the first image, based on a result of the comparing.

Electronic device for recognizing object in image, and operation method thereof

Provided is an image processing method according to an embodiment, which includes: obtaining a label of a first image by inputting the first image to a recognition model; obtaining reference style data for a target reference image to which a visual sentiment label is assigned, the visual sentiment label being the same as the obtained label from among visual sentiment labels pre-assigned to reference images; generating second style data based on first style data for the first image and the obtained reference style data; and generating a second image based on the generated second style data.

Image processing apparatus and method for style transformation

An electronic device and a method for controlling the electronic device are provided. The method for controlling the electronic device includes, based on an occurrence of an event for outputting information being determined, obtaining data for determining a context corresponding to the electronic device, inputting the obtained data to a first model trained by an artificial intelligence algorithm and obtaining information about a person located in a vicinity of the electronic device, inputting the obtained information about the person and information about the event to a second model trained by an artificial intelligence algorithm and obtaining output information corresponding to the event, and providing the obtained output information.

Electronic device and method for controlling the electronic device to provide output information of event based on context

Emotion information is obtained by an electronic device in order to improve communication between a person and the electronic device. Multimedia data is obtained regarding a person, predicted values for the person are obtained by applying the multimedia data to neural network models, and emotion information of the person is obtained by applying the predicted values to a weight model. Then, feedback information is obtained from the person with respect to the first emotion information of the person. Finally, the weight model is updated by using the feedback information. Subsequently, when multimedia data are again obtained regarding the person, new predicted values for the person are obtained by applying later multimedia data the plurality of neural network models, and emotion information of the person is again obtained, but this time using the weight model updated using the feedback information.

Electronic device and method of obtaining emotion information

A display apparatus and a controlling method thereof. The display apparatus may include: a camera, a display, and a processor, where the processor controls the display to display a content, identifies a user interest object in the content displayed on the display based on a user image captured by the camera, and identifies a user preference for the content based on a degree of similarity between information on emotion of the user interest object and information on user emotion.

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Suwon-si, South Korea

Yehoon Kim