Loss Functions
FLIP
Introduced by Andersson et al. in FLIP: A Difference Evaluator for Alternating Imageshttps://developer.nvidia.com/blog/flip-a-difference-evaluator-for-alternating-images/
Source: FLIP: A Difference Evaluator for Alternating ImagesPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Classification | 8 | 4.60% |
| Sentence | 7 | 4.02% |
| Self-Supervised Learning | 6 | 3.45% |
| Adversarial Robustness | 6 | 3.45% |
| Denoising | 5 | 2.87% |
| Adversarial Attack | 4 | 2.30% |
| Sentiment Analysis | 4 | 2.30% |
| Classification | 4 | 2.30% |
| Fairness | 3 | 1.72% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
