Name
Abstract | ||
|---|---|---|
The high similarities of different real-world vehicles and great diversities of the acquisition views pose grand challenges to vehicle re-identification (ReID), which traditionally maps the vehicle images into a high-dimensional embedding space for distance optimization, vehicle discrimination, and identification. To improve the discriminative capability and robustness of the ReID algorithm, we pr... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TIP.2019.2902112 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
Gallium nitride,Space vehicles,Training,Generative adversarial networks,Task analysis,Image generation,Licenses | Training set,Embedding,Task analysis,Pattern recognition,Robustness (computer science),Grand Challenges,Artificial intelligence,Discriminative model,Machine learning,Mathematics,Adversarial system,Learning network | Journal |
Volume | Issue | ISSN |
28 | 8 | 1057-7149 |
Citations | PageRank | References |
14 | 0.68 | 20 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lou Yihang | 1 | 75 | 9.57 |
| Bai Yan | 2 | 18 | 1.75 |
| Jun Liu | 3 | 671 | 30.44 |
| Shiqi Wang | 4 | 1281 | 120.37 |
| Ling-yu Duan | 5 | 1770 | 124.87 |