MAPPING MACHINE LEARNING ACTIVATION DATA TO A REPRESENTATIVE VALUE PALETTE

    公开(公告)号:US20220207408A1

    公开(公告)日:2022-06-30

    申请号:US17134804

    申请日:2020-12-28

    Abstract: Mapping machine learning activation data to a representative value palette, including: selecting, from a plurality of activation values of a model execution, a plurality of representative values; identifying, for each activation value of the plurality of activation values, a representative value of the plurality of representative values; calculating, for each activation value of the plurality of activation values, a corresponding residual value as a difference between an activation value and a corresponding representative value; and storing, for each activation value of the plurality of activation values, the corresponding residual value and an index of the corresponding representative value.

    REFERENCE FRAME DETECTION USING SENSOR METADATA

    公开(公告)号:US20220094908A1

    公开(公告)日:2022-03-24

    申请号:US17031343

    申请日:2020-09-24

    Abstract: Reference frame detection using sensor metadata, including: storing a plurality of first frames each corresponding to first metadata, wherein the first metadata for each first frame of the plurality of first frames is based on first sensor data from one or more sensors; generating a second frame corresponding to second metadata based on the one or more sensors; identifying, based on the first metadata of the plurality of first frames and the second metadata, a reference frame of the plurality of first frames; and encoding the second frame based on the reference frame.

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