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公开(公告)号:US11270218B2
公开(公告)日:2022-03-08
申请号:US16456456
申请日:2019-06-28
发明人: Ming-Jung Seow , Gang Xu , Tao Yang , Wesley Kenneth Cobb
摘要: Techniques are disclosed for generating a sequence of symbols based on input data for a neuro-linguistic model. The model may be used by a behavior recognition system to analyze the input data. A mapper component of a neuro-linguistic module in the behavior recognition system receives one or more normalized vectors generated from the input data. The mapper component generates one or more clusters based on a statistical distribution of the normalized vectors. The mapper component evaluates statistics and identifies statistically relevant clusters. The mapper component assigns a distinct symbol to each of the identified clusters.
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公开(公告)号:US10853661B2
公开(公告)日:2020-12-01
申请号:US16120943
申请日:2018-09-04
发明人: Gang Xu , Tao Yang , Ming-Jung Seow
IPC分类号: G06K9/00 , G10L15/16 , G10L15/197 , G06N20/00 , G06F40/20
摘要: Techniques are disclosed to optimize feature selection in generating betas for a feature dictionary of a neuro-linguistic Cognitive AI System. A machine learning engine receives a sample vector of input data to be analyzed by the neuro-linguistic Cognitive AI System. The neuro-linguistic Cognitive AI System is configured to generate multiple betas for each of a plurality of sensors. The machine learning engine identifies a sensor specified in the sample vector and selects optimization parameters for generating betas based on the identified sensor.
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