- 专利标题: Motion Compensation and Refinement in Recurrent Neural Networks
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申请号: US17649791申请日: 2022-02-02
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公开(公告)号: US20220269921A1公开(公告)日: 2022-08-25
- 发明人: Igor Kossaczky , Sven Labusch , Mirko Meuter
- 申请人: Aptiv Technologies Limited
- 申请人地址: BB St. Michael
- 专利权人: Aptiv Technologies Limited
- 当前专利权人: Aptiv Technologies Limited
- 当前专利权人地址: BB St. Michael
- 优先权: EP21158127.7 20210219
- 主分类号: G06N3/04
- IPC分类号: G06N3/04 ; G06V20/58 ; G06V10/82 ; G07C5/08
摘要:
Provided is a method and system for tracking a motion of information in a spatial environment of a vehicle. Sensor-based data regarding the spatial environment is acquired for a plurality of timesteps, the sensor-based data defining the information in spatially resolved cells. For each of the timesteps, the sensor-based data is input into a recurrent neural network, RNN, having one or more internal memory states. For each of the timesteps, the internal states of the RNN are transformed by using a motion map describing a speed and/or a direction of motion of the information of the spatially resolved cells individually. For each of the plurality of timesteps, the transformed internal states are used in a processing of the RNN to track the motion of the information in the environment of the moving vehicle.