Name
Title | ||
|---|---|---|
Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains |
Abstract | ||
|---|---|---|
Few-shot classification aims to carry out classification given only few labeled examples for the categories of interest. Though several approaches have been proposed, most existing few-shot learning (FSL) models assume that base and novel classes are drawn from the same data domain. When it comes to recognizing novel-class data in an unseen domain, this becomes an even more challenging task of dom... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICIP42928.2021.9506141 | 2021 IEEE International Conference on Image Processing (ICIP) |
Keywords | DocType | ISBN |
Training,Visualization,Image recognition,Target recognition,Conferences,Data models,Task analysis | Conference | 978-1-6654-4115-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan-Chia Cheng | 1 | 0 | 0.34 |
| Ci-Siang Lin | 2 | 0 | 1.35 |
| Fu-En Yang | 3 | 12 | 2.60 |
| Yu-Chiang Frank Wang | 4 | 914 | 61.63 |