Samsung Electronics Co., Ltd.

Jun-ik Jang

So-jung Yun

Ye-hoon Kim

Han-sung Lee

Soon-hyuk Hong

Jin-ho Lee

Do-Jun Yang

Chan-jong Park

Chan-ju Park

Lei Zhang

Jae-il Jung

An image processing apparatus and an image processing method for estimating a region of interest based on information of interest learned by a data recognition model satisfying a certain condition from among a plurality of data recognition models and for setting a focus are provided. The image processing apparatus includes estimating a region of interest by using a rule-based algorithm or an artificial intelligence (AI) algorithm. When estimating a region of interest by using an AI algorithm, the image processing apparatus may estimate a region of interest by using a machine learning algorithm, a neural network algorithm, or a deep learning algorithm.

Apparatus and method for processing image

An electronic apparatus and an operating method are provided. The electronic apparatus includes a storage, at least one sensor, and at least one processor configured to execute stored instructions to while the electronic apparatus is moving, capture a surrounding image by using the at least one sensor, when an unable-to-move situation occurs while the electronic apparatus is moving, generate context data including a surrounding image captured within a predetermined time from a time when the unable-to-move situation has occurred, store, in the storage, the generated context data corresponding to the unable-to-move situation having occurred, and learn the stored context data by using one or more data recognition models.

Electronic device and operation method therefor

Provided is an artificial intelligence (AI) system for simulating human brain functions such as perception and judgment by using a machine learning algorithm such as deep learning, and an application thereof. Provided is a device and method for recommending products to a user on the basis of facial expression information of the user through the AI system. The method, performed by the device, of recommending products includes: displaying a product selected by the user; obtaining user's facial expression information with respect to the displayed product; determining the user's satisfaction with the displayed product based on the obtained user's facial expression information; selecting a product set to be recommended to the user from among a plurality of product sets based on the determined user's satisfaction; and displaying at least one product included in the selected product set.

Device and method for recommending product

Disclosed is an electronic device. An electronic device according to one embodiment may comprise: a communication module; a sensor module which acquires movement information of the electronic device and image information of the place where the electronic device is moving; a memory which stores space information corresponding to the place where the electronic device is moving; and a processor which uses the movement information and space information to determine a plurality of first candidate locations, within the place, corresponding to the electronic device, and then, on the basis of the image information and the plurality of first candidate locations, determines whether the location accuracy corresponding to the plurality of first candidate locations is smaller than a valid value, and, on the basis of the result of the determination, uses the electronic device or an external server to acquire at least one second candidate location from among the plurality of first candidate locations, and uses the acquired at least one second candidate location to determine an estimated location for the electronic device.

Electronic device, external server, and method for controlling same

An electronic apparatus is provided. The electronic apparatus includes at least one processor configured to detect, by a sensor, a driving state of a vehicle or a driving state of another vehicle in a vicinity of the vehicle while the vehicle is being driven, obtain state data including the driving state of the vehicle and the driving state of the other vehicle, and use at least one data recognition model to determine a dangerous situation of the vehicle after a certain period of time while the vehicle is being driven, based on the obtained state data. The electronic apparatus may predict a dangerous situation of the vehicle by using a rule-based algorithm or an artificial intelligence (AI) algorithm. The electronic apparatus predicts the dangerous situation of the vehicle by using at least one of machine learning, a neural network, and a deep learning algorithm.

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Bucheon-si, South Korea

Jun-ik Jang