Robust lane recognition for autonomous driving
Research output: Contribution to conferences › Paper › Contributed › peer-review
Contributors
Details
| Original language | English |
|---|---|
| Pages | 1-6 |
| Number of pages | 6 |
| Publication status | Published - 2017 |
| Peer-reviewed | Yes |
Conference
| Title | 2017 Conference on Design and Architectures for Signal and Image Processing |
|---|---|
| Abbreviated title | DASIP 2017 |
| Duration | 27 - 29 September 2017 |
| City | Dresden |
| Country | Germany |
External IDs
| Scopus | 85044295283 |
|---|---|
| ORCID | /0000-0003-2571-8441/work/142240423 |
Keywords
Research priority areas of TU Dresden
DFG Classification of Subject Areas according to Review Boards
Keywords
- automobiles, image sensors, mobile robots, object detection, traffic cones, road, driving simulator, robust lane recognition, autonomous cars, time 0.55 ms, Cameras, Robustness, Object detection, Automobiles, Roads, Sensors, Viola-Jones, Lane Recognition, road vehicles, traffic engineering computing, Viola-Jones method, emergency situation, high detection rate, Viola-Jones object detection method, robust autonomous driving algorithm, Algorithm design and analysis, Autonomous Driving, Object Detection, Machine Learning