- 专利标题: FEDERATED LEARNING FOR CONNECTED CAMERA APPLICATIONS IN VEHICLES
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申请号: US17647524申请日: 2022-01-10
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公开(公告)号: US20230221942A1公开(公告)日: 2023-07-13
- 发明人: Wende Zhang , Esther Anderson , Mark T Gaylord , Robert A Dziurda
- 申请人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 申请人地址: US MI Detroit
- 专利权人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 当前专利权人: GM GLOBAL TECHNOLOGY OPERATIONS LLC
- 当前专利权人地址: US MI Detroit
- 主分类号: G06F8/65
- IPC分类号: G06F8/65 ; G06F8/71 ; G06K9/62
摘要:
Vehicles and related systems and methods are provided for classifying detected objects in a location-dependent manner using localized models in a federated learning environment. A method involves obtaining sensor data for a detected object external to the vehicle from a sensor of a vehicle, obtaining location data associated with the detected object, obtaining a local classification model associated with an object type, assigning the object type to the detected object based on an output by the local classification model as a function of the sensor data and the location data using the local classification model, and initiating an action at the vehicle responsive to assigning the object type to the detected object.
公开/授权文献
- US11853741B2 Federated learning for connected camera 公开/授权日:2023-12-26
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