公开(公告)号：US20250069380A1

公开(公告)日：2025-02-27

申请号：US18238004

申请日：2023-08-25

Applicant: NXP B.V.

Inventor： Tunc Alkanat ,  Ashish Pandharipande

IPC: G06V10/82 ,  G01S13/89 ,  G06V10/75

Abstract: Techniques for using machine learning to produce sensor data from vision sensor data are disclosed. By using a limited amount of sensor data together with vision sensor data, a deep learning network can be trained to produce estimated sensor point cloud distributions from, e.g., vision sensor data alone. Using a deep learning network trained in this way, vehicles with limited or no other sensor functionality can be equipped with a camera to produce estimated sensor point cloud distributions. The estimated sensor point cloud distributions can then be used to improve vehicle safety through vehicle controls or driver notifications and/or to produce enhanced sensor data.

公开(公告)号：US20250069408A1

公开(公告)日：2025-02-27

申请号：US18238007

申请日：2023-08-25

Applicant: NXP B.V.

Inventor： Tunc Alkanat ,  Ashish Pandharipande

IPC: G06V20/58 ,  G01S13/89 ,  G06V10/75 ,  G06V10/82

Abstract: Techniques for using machine learning to produce vehicle location sensor data from vision sensor data are disclosed. By using a limited amount of vehicle location sensor data together with vision sensor data, a deep learning network can be trained to produce estimated vehicle location sensor point cloud distributions from, e.g., vision sensor data alone. Using a deep learning network trained in this way, vehicles with limited or no sensor functionality can be equipped with a camera to produce estimated vehicle location sensor point cloud distributions. These estimated vehicle location sensor point cloud distributions can then be compared with general sensor point cloud distributions to improve detection of vehicles, environmental objects, and ghost objects, and subsequently used to improve vehicle safety through vehicle controls or driver notifications and/or to produce enhanced sensor data.