Ensemble learning for cross-range 3D object detection in driver assist and autonomous driving systems
US12243158B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 29, 2020 |
| Grant date | Mar 4, 2025 |
| Priority date | — |
| Expiry date | Sep 21, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30261
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A cross-range 3D object detection method and system operable for training a 3D object detection model with N sub-groups of a point cloud corresponding to N detection distance ranges to form N 3D object detection models forming an ensemble 3D object detection model. Training the 3D object detection model with the N sub-groups of the point cloud corresponding to the N detection distance ranges includes training the 3D object detection model progressively from distant to near. Training the 3D object detection model with the N sub-groups of the point cloud corresponding to the N detection distance ranges includes, each time the 3D object detection model converges, saving resulting weights and adding a corresponding network to the ensemble 3D object detection model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.