Joachim Pehserl
21Patents
3h-index
34Co-inventors
59Inventor score
Filing activity: Jan 16, 2009 → Oct 24, 2023
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US11532168B2 | Multi-view deep neural network for LiDAR perception | Physics | 5 | Active |
| US11885907B2 | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications | Physics | 4 | Active |
| US12051206B2 | Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications | Physics | 3 | Active |
| US11531088B2 | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications | Physics | 2 | Active |
| US8428088B2 | Synchronization of multiple data sources to a common time base | Electricity | 2 | Active |
| US7974314B2 | Synchronization of multiple data source to a common time base | Electricity | 1 | Active |
| US12344270B2 | Hazard detection using occupancy grids for autonomous systems and applications | Performing Operations; Transporting | 1 | Active |
| US10147235B2 | AR display with adjustable stereo overlap zone | Electricity | 1 | Active |
| US11906660B2 | Object detection and classification using LiDAR range images for autonomous machine applications | Physics | 1 | Active |
| US11915493B2 | Multi-view deep neural network for LiDAR perception | General | 0 | Revoked |
| US12235353B2 | Particle-based hazard detection for autonomous machine | Physics | 0 | Active |
| US12399253B2 | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications | Physics | 0 | Active |
| US12373960B2 | Dynamic object detection using LiDAR data for autonomous machine systems and applications | Physics | 0 | Active |
| US12050285B2 | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications | Physics | 0 | Active |
| US12332614B2 | Combining rule-based and learned sensor fusion for autonomous systems and applications | Performing Operations; Transporting | 0 | Active |
| US11954914B2 | Belief propagation for range image mapping in autonomous machine applications | Physics | 0 | Active |
| US8244431B2 | Determining velocity using multiple sensors | Physics | 0 | Active |
| US11960026B2 | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications | General | 0 | Revoked |
| US12072443B2 | Segmentation of lidar range images | Physics | 0 | Active |
| US12164059B2 | Top-down object detection from LiDAR point clouds | Physics | 0 | Active |
| US12080078B2 | Multi-view deep neural network for LiDAR perception | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.