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公开(公告)号：US12094154B2
公开(公告)日：2024-09-17
申请号：US17704894
申请日：2022-03-25
Inventor： Yuntae Kim , Sanghoon Sull , Seongwook Yoon , Donghoon Sagong , Heejeong Lim , Hojin Ju , Jaehwan Pi
CPC classification number: G06T7/70 , G06T7/277 , G06T2207/20081 , G06T2207/20084
Abstract: An electronic device includes a memory storing a plurality of motion prediction models, and a processor configured to estimate a current pose of the electronic device based on external data; predict a first motion of the electronic device at a future first prediction time through a first model in which the plurality of motion prediction models are combined for the future first prediction time, and calculate a first pose of the electronic device at the first prediction time based on the current pose and the first motion; and predict a second motion of the electronic device at a future second prediction time through a second model in which the plurality of motion prediction models are combined for the future second prediction time, and calculate a second pose of the electronic device at the second prediction time based on the first pose and the second motion.
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公开(公告)号：US12158869B2
公开(公告)日：2024-12-03
申请号：US18149991
申请日：2023-01-04
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Seongwook Yoon , Sanghoon Sull , Jaehyun Kim , Heejeong Lim
IPC: G06F16/215 , G06F16/2458
Abstract: A method of obtaining and imputing missing data and a measurement system having the same are disclosed. The method includes obtaining measurement values of measurement variables, among z variables corresponding to z components of a measurement object, wherein z is a natural number greater than 1, and the z variables of the measurement object include measurement variables and missing variables which are not measured, and the measurement variables are of an amount less than z; generating missing data having the measurement variables with the measurement values and the missing variables with missing values in the z components, wherein each of the missing values is predetermined value indicating that a missing variable has not been measured; generating k pieces of final imputation data having k final imputation values, by using the missing data, wherein k is a natural number greater than 1, each of the k final imputation values are in the z components, and using the missing data includes performing multiple imputations on the missing data; and generating average data having average component values in the z components, wherein each of the average component values in a component is an average value of the k final imputation values of the k pieces of final imputation data in the component, and selecting, in each of the z components, a next measurement variable, wherein a difference value between a final imputation values and an average component value, of the next measurement variable, is larger than a difference value of the missing variables.
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公开(公告)号：US20230214371A1
公开(公告)日：2023-07-06
申请号：US18149991
申请日：2023-01-04
Inventor： Seongwook YOON , Sanghoon Sull , Jaehyun Kim , Heejeong Lim
IPC: G06F16/215 , G06F16/2458
CPC classification number: G06F16/215 , G06F16/2462
Abstract: A method of obtaining and imputing missing data and a measurement system having the same are disclosed. The method. includes obtaining measurement values of measurement variables, among z variables corresponding to z components of a measurement object, wherein z is a natural number greater than 1, and the z variables of the measurement object include measurement variables and missing variables which are not measured, and the measurement variables are of an amount less than z; generating missing data having the measurement variables with the measurement values and the missing variables with missing values in the z components, wherein each of the missing values is predetermined value indicating that a missing variable has not been measured; generating k pieces of final imputation data having k final imputation values, by using the missing data, wherein k is a natural number greater than 1, each of the k final imputation values are in the z components, sing the missing data includes performing multiple imputations on the missing data; and generating average data having average component values in the z components, wherein each of the average component values in a component is an average value of the k final imputation values of the k pieces of final imputation data in the component, and selecting, in each of the z components, a next measurement variable, wherein a difference value between a final imputation values and an average component value, of the next measurement variable, is larger than a difference value of the missing variables.
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公开(公告)号：US20230064242A1
公开(公告)日：2023-03-02
申请号：US17704894
申请日：2022-03-25
Inventor： Yuntae KIM , Sanghoon Sull , Seongwook Yoon , Donghoon Sagong , Heejeong Lim , Hojin Ju , Jaehwan Pi
Abstract: An electronic device includes a memory storing a plurality of motion prediction models, and a processor configured to estimate a current pose of the electronic device based on external data; predict a first motion of the electronic device at a future first prediction time through a first model in which the plurality of motion prediction models are combined for the future first prediction time, and calculate a first pose of the electronic device at the first prediction time based on the current pose and the first motion; and predict a second motion of the electronic device at a future second prediction time through a second model in which the plurality of motion prediction models are combined for the future second prediction time, and calculate a second pose of the electronic device at the second prediction time based on the first pose and the second motion.
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