Samsung Electronics Co., Ltd.

Junik Jang

Chanwon Seo

Yehoon Kim

Sojung Yun

Jaeil Jung

Jonghee Hong

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

According to certain embodiments, an electronic apparatus comprises: a memory storing a generator previously trained to generate a prediction image based on one or more input images; and a processor configured to: acquire feature data from a plurality of image frames input through at least one layer included in the generator, extract feature data corresponding to change over time from the feature data acquired through an attention layer included in the generator, and acquire a prediction image frame by inputting the extracted feature data to at least one other layer included in the generator.

Device for generating prediction image on basis of generator including concentration layer, and control method therefor

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.

A method for analyzing an image for anomaly detection includes obtaining a first image. The method also includes generating a second image by auto-encoding the first image. The method additionally includes extracting first and second feature vectors from the first and second images, respectively. The method further includes filtering each of the first and second feature vectors by using a filtering vector generated based on first distance values between first respective elements of the first and second feature vectors. Additionally, the method includes determining whether there is an anomaly in the first image based on second distance values between second respective elements of the filtered first and second feature vectors.

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Suwon-si, South Korea

Junik Jang