Name
Title | ||
|---|---|---|
Hierarchical deep transfer learning for fine-grained categorization on micro datasets |
Abstract | ||
|---|---|---|
•We present a novel discriminative model to learn similarity measurement between source domain and target domain.•We freeze part of the network layers to extract well-defined representations from source domain to target domain.•We use auxiliary images labelled by perspective-class to improve categorization performance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jvcir.2019.05.002 | Journal of Visual Communication and Image Representation |
Keywords | Field | DocType |
Fine-grained categorization,Convolutional neural network,Transfer learning,Multi-task learning,Model compression | Cohesion (chemistry),Categorization,Annotation,Pattern recognition,Subject-matter expert,Convolutional neural network,Transfer of learning,Artificial intelligence,Discriminative model,Mathematics,Minimum bounding box | Journal |
Volume | ISSN | Citations |
62 | 1047-3203 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronggui Wang | 1 | 44 | 10.06 |
| Xuchen Yao | 2 | 0 | 0.34 |
| Juan Yang | 3 | 40 | 10.74 |
| Lixia Xue | 4 | 8 | 4.56 |
| Min Hu | 5 | 31 | 12.64 |