Name
Abstract | ||
|---|---|---|
In autonomous driving, the interaction of trajectory prediction has always served as the core. Designing a model to better capture the associated interactive information to improve the prediction accuracy is the key to the safety of autonomous driving. In order to solve this problem, this paper proposes a Graph Partition Convolution Neural Network (GP-CNN) to effectively focus on the interaction o... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICTAI52525.2021.00074 | 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI) |
Keywords | DocType | ISSN |
Legged locomotion,Convolution,Neural networks,Predictive models,Feature extraction,Trajectory,Safety | Conference | 1082-3409 |
ISBN | Citations | PageRank |
978-1-6654-0898-1 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ruiyang Wang | 1 | 0 | 0.34 |
| Ming Li | 2 | 0 | 1.01 |
| Pin Zhang | 3 | 0 | 0.34 |
| Fan Wen | 4 | 0 | 0.34 |