Name
Abstract | ||
|---|---|---|
Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such as text, image, video, audio, and 3-D model). However, existing methods based on a deep neural network often face the challenge of insufficient cross-modal training data, which limits the training effectiveness and easily leads to overfitting. Transfer learning is usually adopted for relieving the problem... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TCYB.2018.2879846 | IEEE Transactions on Cybernetics |
Keywords | Field | DocType |
Semantics,Training data,Knowledge transfer,Training,Correlation,Task analysis,Solid modeling | Computer science,Transfer of learning,Knowledge transfer,Theoretical computer science,Artificial intelligence,Boosting (machine learning),Overfitting,Discriminative model,Subnetwork,Machine learning,Semantics,Feature learning | Journal |
Volume | Issue | ISSN |
50 | 3 | 2168-2267 |
Citations | PageRank | References |
11 | 0.48 | 37 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Huang | 1 | 11 | 0.48 |
| Yuxin Peng | 2 | 1122 | 74.90 |
| Mingkuan Yuan | 3 | 71 | 3.75 |