Electronic apparatus, control method thereof and electronic system

    公开(公告)号:US11455706B2

    公开(公告)日:2022-09-27

    申请号:US17464119

    申请日:2021-09-01

    Abstract: An electronic apparatus is disclosed. The electronic apparatus includes: a memory configured to store a downscaling network of a first artificial intelligence model, a communication interface comprising communication circuitry, and a processor connected to the memory and the communication interface and configured to control the electronic apparatus, wherein the processor is configured to: obtain an output image in which an input image is downscaled by inputting the input image the downscaling network, control the communication interface to transmit the output image to another electronic apparatus, and wherein the first artificial intelligence model is configured to be learned based on: a sample image, a first intermediate image obtained by inputting the sample image to the downscaling network, a first final image obtained by inputting the first intermediate image to an upscaling network of the first artificial intelligence model, a second intermediate image in which the sample image is downscaled by a legacy scaler, and a second final image in which the first intermediate image is upscaled by the legacy scaler.

    Substrate testing apparatus
    4.
    发明授权

    公开(公告)号:US11467205B2

    公开(公告)日:2022-10-11

    申请号:US17338312

    申请日:2021-06-03

    Abstract: A substrate testing apparatus configured to perform a hot electron analysis (HEA) test for analyzing a stand-by failure in a substrate includes a heating chuck having a first surface configured to support the substrate and a second surface opposite to the first surface. The heating chuck is configured to heat the substrate and has an aperture passing through the first surface and the second surface. A substrate moving device moves the substrate on the heating chuck in a lateral direction. A camera is under the heating chuck and photographs the substrate, which is exposed by the heating chuck aperture.

    AI encoding apparatus and operation method of the same, and AI decoding apparatus and operation method of the same

    公开(公告)号:US12073595B2

    公开(公告)日:2024-08-27

    申请号:US17522579

    申请日:2021-11-09

    CPC classification number: G06T9/002 G06N3/045 G06T3/4046 G06T7/0002

    Abstract: An artificial intelligence (AI) encoding apparatus includes at least one processor configured to: determine a downscaling target, based on a target resolution for a first image, obtain the first image by AI-downscaling an original image using an AI-downscaling neural network corresponding to the downscaling target, generate image data by encoding the first image, select AI-upscaling neural network set identification information, based on the target resolution of the first image, characteristic information of the original image, and a target detail intensity, generate AI data including the target resolution of the first image, bit depth information of the first image, the AI-upscaling neural network set identification information, and encoding control information, and generate AI encoding data including the image data and the AI data; and a communication interface configured to transmit the AI encoding data to an AI decoding apparatus, wherein the AI data includes information about an AI-upscaling neural network corresponding to the AI-downscaling neural network.

    Method of controlling external electronic device and electronic device for supporting same

    公开(公告)号:US11128713B2

    公开(公告)日:2021-09-21

    申请号:US16750416

    申请日:2020-01-23

    Abstract: Disclosed is an electronic device including: a communication circuit; a processor; and a memory, wherein the memory stores instructions which, when executed, cause the processor to control the electronic device to: acquire first information on types of objects disposed within a first space and second information on locations of the objects in a first direction, select a target object, generate first name of the target object based on information on a type of the target object in the first information, generate second name of at least one counterpart object based on information on a type of the counterpart object disposed around the target object in the first information, determine a relative location relation between the target object and the at least one counterpart object based on the second information, and generate third name of the target object based on the first name, the second name, and the relative location relation.

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