Name
Abstract | ||
|---|---|---|
Vehicle taillight detection is essential to analyze and predict driver intention in collision avoidance systems. In this article, we propose an end-to-end framework that locates the rear brake and turn signals from video stream in real-time. The system adopts the fast YOLOv3-tiny as the backbone model and three improvements have been made to increase the detection accuracy on taillight semantics, ... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TITS.2020.3027421 | IEEE Transactions on Intelligent Transportation Systems |
Keywords | DocType | Volume |
Brakes,Deep learning,Feature extraction,Object detection,Real-time systems,Image color analysis,Detectors | Journal | 22 |
Issue | ISSN | Citations |
7 | 1524-9050 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Qiaohong Li | 1 | 0 | 0.34 |
| Sahil Garg | 2 | 267 | 40.16 |
| Jiangtian Nie | 3 | 97 | 10.96 |
| Xiang Li | 4 | 0 | 0.34 |
| Ryan Wen Liu | 5 | 16 | 3.73 |
| zhiguang cao | 6 | 68 | 11.12 |
| Mohammod Shamim Hossain | 7 | 268 | 34.68 |