Image processing apparatuses including CNN-based in-loop filter

    公开(公告)号:US12010302B2

    公开(公告)日:2024-06-11

    申请号:US18088615

    申请日:2022-12-26

    Inventor: Mun Churl Kim

    Abstract: Disclosed according to one exemplary embodiment includes not limited to: a filtering unit configured to generate filtering information by filtering a residual image corresponding to a difference between an original image and a prediction image; an inverse filtering unit configured to generate inverse filtering information by inversely filtering the filtering information; an estimator configured to generate the prediction image based on the original image and reconstruction information; a CNN-based in-loop filter configured to receive the inverse filtering information and the prediction image and to output the reconstruction information; and an encoder configured to perform encoding based on the filtering information and information of the prediction image, and wherein the CNN-based in-loop filter is trained for each of the plurality of artefact sections according to an artefact value or for each of the plurality of quantization parameter sections according to a quantization parameter.

    SYSTEM AND METHOD FOR AUTOMATING SELF-EXPERIMENTATION BASED ON LIFELOG DATA FOR HEALTH BEHAVIOR CHANGE

    公开(公告)号:US20240153599A1

    公开(公告)日:2024-05-09

    申请号:US18190784

    申请日:2023-03-27

    CPC classification number: G16H10/20

    Abstract: Disclosed is a system and method for supporting automated self-experimentation based on lifelog data for health behavior change. The system includes a data collection unit configured to collect data related to a user from a plurality of smart terminals and preprocess the data as variables that represent a lifelog of the user; a causal inference unit configured to establish a causal relationship hypothesis between the variables of the user and infer a causal relationship between the variables collected from the user using a statistical analysis method; a variable recommendation unit configured to recommend a variable for verifying the causal relationship through self-experimentation for the user based on an inference result acquired from the causal inference unit and an interaction of the user with the system; and a self-experimentation planning unit configured to plan and conduct an experiment to verify the causal relationship through the self-experimentation for the user.

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