Name
Title | ||
|---|---|---|
Pedestrian Retrieval Using Generated Samples and Multistream Layer in Sensor Networks. |
Abstract | ||
|---|---|---|
In this paper, we propose a novel loss function named the hybrid quadruplet loss (HQL) to utilize the generated samples for pedestrian retrieval in sensor networks. The proposed HQL employs a set of quadruplets in order to maintain an appropriate margin between the real sample and the generated sample, reduce the intra-class variations and enlarge the inter-class variations. By this way, the gener... |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TETCI.2018.2876556 | IEEE Transactions on Emerging Topics in Computational Intelligence |
Keywords | DocType | Volume |
Training,Generative adversarial networks,Gallium nitride,Hybrid power systems,Computational intelligence,Morphology | Journal | 4 |
Issue | Citations | PageRank |
1 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuang Liu | 1 | 36 | 22.95 |
| Xiaolong Hao | 2 | 0 | 1.01 |