公开(公告)号：US20210342637A1

公开(公告)日：2021-11-04

申请号：US17301965

申请日：2021-04-20

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06K9/62 ,  G05D1/02 ,  G06K9/00 ,  G06N3/08

Abstract: 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.

公开(公告)号：US11748620B2

公开(公告)日：2023-09-05

申请号：US17301965

申请日：2021-04-20

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06N3/08 ,  G05D1/02 ,  G06V20/56 ,  G06F18/28 ,  G16Y20/10 ,  G06N3/04

CPC classification number: G06N3/08 ,  G05D1/0221 ,  G06F18/28 ,  G06V20/588 ,  G16Y20/10 ,  G06N3/04

Abstract: 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.

公开(公告)号：US12223428B2

公开(公告)日：2025-02-11

申请号：US18459954

申请日：2023-09-01

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06N3/08 ,  G05D1/00 ,  G06F18/28 ,  G06V20/56 ,  G16Y20/10 ,  G06N3/04

Abstract: 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.

公开(公告)号：US20250124286A1

公开(公告)日：2025-04-17

申请号：US18991094

申请日：2024-12-20

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06N3/08 ,  G06F18/28 ,  G06N3/04 ,  G06V20/56 ,  G16Y20/10

Abstract: 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.

公开(公告)号：US20240070460A1

公开(公告)日：2024-02-29

申请号：US18459954

申请日：2023-09-01

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06N3/08 ,  G05D1/02 ,  G06F18/28 ,  G06V20/56 ,  G16Y20/10

CPC classification number: G06N3/08 ,  G05D1/0221 ,  G06F18/28 ,  G06V20/588 ,  G16Y20/10 ,  G06N3/04

Abstract: 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.

公开(公告)号：US10997461B2

公开(公告)日：2021-05-04

申请号：US16265729

申请日：2019-02-01

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06K9/62 ,  G05D1/02 ,  G06K9/00 ,  G06N3/08 ,  G06N3/04

Abstract: 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.

公开(公告)号：US20200250473A1

公开(公告)日：2020-08-06

申请号：US16265729

申请日：2019-02-01

Applicant: Tesla, Inc.

Inventor： Ashok Kumar Elluswamy ,  Matthew Bauch ,  Christopher Payne ,  Andrej Karpathy ,  Joseph Polin

IPC: G06K9/62 ,  G06K9/00 ,  G06N3/08 ,  G05D1/02

Abstract: 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.