Transform coefficient coding using level maps

    公开(公告)号:US10244261B2

    公开(公告)日:2019-03-26

    申请号:US15415974

    申请日:2017-01-26

    Applicant: GOOGLE INC.

    Abstract: A method for encoding a transform block in an encoded video bitstream is provided. The method includes encoding a non-zero map indicating positions of the transform block containing non-zero transform coefficients, encoding a respective lower-range level map, and encoding a coefficient residual map. A lower-range level map indicates which values of the non-zero transform coefficients are equal to and which are greater than the map level. Each residual coefficient of the coefficient residual map corresponds to a respective non-zero transform coefficient of the transform block having an absolute value exceeding the maximum map level. An apparatus including a processor and a memory for decoding a transform block is also provided. The memory includes instructions executable by the processor to decode, a non-zero map, decode lower-range level maps up to a maximum map level, and decode a coefficient residual map.

    EVALUATING MODELS THAT RELY ON AGGREGATE HISTORICAL DATA

    公开(公告)号:US20190087469A1

    公开(公告)日:2019-03-21

    申请号:US15707594

    申请日:2017-09-18

    Applicant: Google Inc.

    Abstract: Systems and methods for model validation includes generating a first and a second time series of segmentation states for a data set representative of a simulated population, e.g., a collection of membership counts corresponding to respective segments of the simulated population. The first and second time series of segmentation states are generated by respectively processing the data set through a first and a second simulation each comprising iterative application of a plurality of event functions. The first and the second simulation differ in at least one capacity, e.g., one including a first event function configured with a first parameter, and the second not. Analysis of differences between the first and second time series may be compared to analysis of one of the time series using a subject model. The comparison is then used to validate the model or demonstrate accuracies, inaccuracies, and/or model bias with respect to a performance metric.

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