- 专利标题: System and Method for Evaluating Defensive Performance using Graph Convolutional Network
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申请号: US17649970申请日: 2022-02-04
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公开(公告)号: US20220253679A1公开(公告)日: 2022-08-11
- 发明人: Paul David Power , Thomas Seidl , Michael Stöckl , Daniel Edison Marley
- 申请人: STATS LLC
- 申请人地址: US IL Chicago
- 专利权人: STATS LLC
- 当前专利权人: STATS LLC
- 当前专利权人地址: US IL Chicago
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G06N3/08
摘要:
A computing system retrieves tracking data from a data store. The computing system converts the tracking data into a plurality of graph-based representations. The prediction engine learns to model defensive behavior based on the plurality of graph-based representations. The computing system generates a trained prediction engine based on the learnings. The computing system receives target tracking data for a target event. The target tracking data includes a plurality of target frames. The computing system converts the target tracking data to a plurality of target graph-based representations. The computing system models, via the trained graph neural network, defensive behavior of a team in the target event based on plurality of graph-based representations.
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