Instance segmentation and pose estimation of assembly parts using deep learning and synthetic data generation
| dc.contributor.author | Lecerof, Jonas | |
| dc.contributor.author | Opheim, Torbjörn | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för elektroteknik | sv |
| dc.contributor.examiner | Karayiannidis, Yiannis | |
| dc.contributor.examiner | Åkesson, Knut | |
| dc.date.accessioned | 2019-11-05T09:25:41Z | |
| dc.date.available | 2019-11-05T09:25:41Z | |
| dc.date.issued | 2019 | sv |
| dc.date.submitted | 2019 | |
| dc.identifier.coursecode | EENX30 | sv |
| dc.identifier.uri | https://hdl.handle.net/20.500.12380/300527 | |
| dc.language.iso | eng | sv |
| dc.setspec.uppsok | Technology | |
| dc.title | Instance segmentation and pose estimation of assembly parts using deep learning and synthetic data generation | sv |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.uppsok | H | |
| local.programme | Systems, control and mechatronics (MPSYS), MSc |