- 专利标题: GENERATING GROUND TRUTH FOR MACHINE LEARNING FROM TIME SERIES ELEMENTS
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申请号: US16265729申请日: 2019-02-01
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公开(公告)号: US20200250473A1公开(公告)日: 2020-08-06
- 发明人: Ashok Kumar Elluswamy , Matthew Bauch , Christopher Payne , Andrej Karpathy , Joseph Polin
- 申请人: Tesla, Inc.
- 主分类号: G06K9/62
- IPC分类号: G06K9/62 ; G06K9/00 ; G06N3/08 ; G05D1/02
摘要:
Sensor data, including a group of time series elements, is received. A training data set is determined, including by determining for at least a selected time series element in the group of time series elements a corresponding ground truth. The corresponding ground truth is based on a plurality of time series elements in the group of time series elements. A processor is used to train a machine learning model using the training dataset.
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