Transformation-Based Data Synthesis for Limited Sample Scenario
We consider a challenging learning scenario where neither pretext training nor auxiliary data are available except for small training samples. We call this a transfer-free scenario where we cannot access any transferable knowledge or data. Our proposal for resolving this issue is to learn a pair-wis...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10781377/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|