Camera-Radar Sensor Fusion using Deep Learning. A frustum proposal-based 3D object detection network for multi stage fusion in autonomous driving
| dc.contributor.author | Brandes, Julian | |
| dc.contributor.author | Kübel, Johannes | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för elektroteknik | sv |
| dc.contributor.examiner | Wymeersch, Henk | |
| dc.date.accessioned | 2022-09-01T07:11:31Z | |
| dc.date.available | 2022-09-01T07:11:31Z | |
| dc.date.issued | 2022 | sv |
| dc.date.submitted | 2020 | |
| dc.identifier.coursecode | EENX30 | sv |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/305503 | |
| dc.language.iso | eng | sv |
| dc.setspec.uppsok | Technology | |
| dc.title | Camera-Radar Sensor Fusion using Deep Learning. A frustum proposal-based 3D object detection network for multi stage fusion in autonomous driving | sv |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.uppsok | H | |
| local.programme | Systems, control and mechatronics (MPSYS), MSc |