Name
Abstract | ||
|---|---|---|
•This work is the _rst overall review of recent deep learning-based lane detection methods.•Detailed description of representive methods from perpective of computer vision and pattern recognition.•Detailed description of convolution neural networks' architectures and loss functions that used in lanes detector.•Advantages of deep learning-based methods compared with traditional heuristic recognition-based methods.•Current challenges of existing deep learning-based methods and some possible directions to solve the problems. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.patcog.2020.107623 | Pattern Recognition |
Keywords | DocType | Volume |
Lane detection,Deep learning,Semantic segmentation,Instance segmentation | Journal | 111 |
Issue | ISSN | Citations |
1 | 0031-3203 | 3 |
PageRank | References | Authors |
0.40 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jigang Tang | 1 | 3 | 0.40 |
| Songbin Li | 2 | 53 | 4.79 |
| Peng Liu | 3 | 284 | 17.75 |