DISPLAY DEVICE AND OPERATING METHOD OF THE SAME

    公开(公告)号:US20230114954A1

    公开(公告)日:2023-04-13

    申请号:US17887236

    申请日:2022-08-12

    Abstract: A display device for performing image processing by using a neural network including a plurality of layers, may obtain a plurality of pieces of model information respectively corresponding to pixels included in a first image based on object features respectively corresponding to the pixels; identify the plurality of pieces of model information respectively corresponding to the plurality of layers and the pixels input to the neural network based on information about a time point at which each of the pixels is processed in the neural network; update parameters of the plurality of layers, based on the plurality of pieces of model information; and obtain a second image by processing the first image via the plurality of layers to which the updated parameters are applied; and display the second image.

    ELECTRONIC APPARATUS AND CONTROL METHOD THEREOF

    公开(公告)号:US20190281310A1

    公开(公告)日:2019-09-12

    申请号:US16292655

    申请日:2019-03-05

    Abstract: An electronic apparatus is provided. The electronic apparatus includes a storage configured to store a compression rate network model configured to determine a compression rate applied to an image block from among a plurality of compression rates, and a plurality of compression noise removing network models configured to remove compression noise for each of the plurality of compression rates, and a processor configured to: obtain a compression rate of each of a plurality of image blocks included in a frame of a decoded moving picture based on the compression rate network model, obtain the compression rate of the frame based on the plurality of obtained compression rates, and remove compression noise of the frame based on a compression noise removing network model corresponding to the compression rate of the frame from among the plurality of compression noise removing network models. The compression rate network model can be obtained by learning image characteristics of a plurality of restored image blocks corresponding to each of the plurality of compression rates through a first artificial intelligence algorithm, and the plurality of restored image blocks can be generated by encoding a plurality of original image blocks, and decoding the encoded plurality of original image blocks, and the plurality of compression noise removing network models can be obtained by learning a relation between the plurality of original image blocks and the plurality of restored image blocks through a second artificial intelligence algorithm.

    ELECTRONIC APPARATUS AND CONTROLLING METHOD THEREOF

    公开(公告)号:US20240412325A1

    公开(公告)日:2024-12-12

    申请号:US18811938

    申请日:2024-08-22

    Abstract: An electronic apparatus is disclosed. The electronic apparatus includes a memory configured to store a plurality of neural network models, and a processor connected to the memory and control the electronic apparatus in which the processor is configured to obtain a weight map based on an object area included in an input image, and obtain a plurality of images by inputting the input image to each of the plurality of neural network models, and obtain an output image by weighting the plurality of images based on the weight map, and each of the plurality of neural network models is a model trained to upscale an image.

    IMAGE PROCESSING DEVICE AND OPERATING METHOD OF THE SAME

    公开(公告)号:US20250131537A1

    公开(公告)日:2025-04-24

    申请号:US18920493

    申请日:2024-10-18

    Abstract: Provided are an image processing device and an operating method of the same. The image processing device includes a memory storing one or more instructions, and at least one processor processing circuitry, and memory storing one or more instructions that, when executed by the at least one processor individually or collectively, cause the image processing device to obtain a neural network model corresponding to a quality of an input image and viewing information related to the input image. The at least one processor is configured to generate training data, based on the quality of the input image and the viewing information. The at least one processor is configured to train the neural network model by using the training data. The at least one processor is configured to obtain an image quality processed output image from the input image, based on the trained neural network model.

    ELECTRONIC APPARATUS AND CONTROLLING METHOD THEREOF

    公开(公告)号:US20220164923A1

    公开(公告)日:2022-05-26

    申请号:US17221105

    申请日:2021-04-02

    Abstract: An electronic apparatus is disclosed. The electronic apparatus includes a memory configured to store a plurality of neural network models, and a processor connected to the memory and control the electronic apparatus in which the processor is configured to obtain a weight map based on an object area included in an input image, and obtain a plurality of images by inputting the input image to each of the plurality of neural network models, and obtain an output image by weighting the plurality of images based on the weight map, and each of the plurality of neural network models is a model trained to upscale an image.

    DISPLAY DEVICE AND OPERATING METHOD OF THE SAME

    公开(公告)号:US20250124543A1

    公开(公告)日:2025-04-17

    申请号:US18984224

    申请日:2024-12-17

    Abstract: A display device for performing image processing by using a neural network including a plurality of layers, may obtain a plurality of pieces of model information respectively corresponding to pixels included in a first image based on object features respectively corresponding to the pixels; identify the plurality of pieces of model information respectively corresponding to the plurality of layers and the pixels input to the neural network based on information about a time point at which each of the pixels is processed in the neural network; update parameters of the plurality of layers, based on the plurality of pieces of model information; and obtain a second image by processing the first image via the plurality of layers to which the updated parameters are applied; and display the second image.

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