Activation Functions
Features Explanation Method
Introduced by Fuad et al. in Features Understanding in 3D CNNs for Actions Recognition in Video
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Few-Shot Learning | 3 | 12.00% |
| Computational Efficiency | 2 | 8.00% |
| Classification | 2 | 8.00% |
| Management | 1 | 4.00% |
| Imitation Learning | 1 | 4.00% |
| Computed Tomography (CT) | 1 | 4.00% |
| Physical Simulations | 1 | 4.00% |
| Image Super-Resolution | 1 | 4.00% |
| Super-Resolution | 1 | 4.00% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
