Image Data Augmentation
Random Gaussian Blur
Random Gaussian Blur is an image data augmentation technique where we randomly blur the image using a Gaussian distribution.
Image Source: Wikipedia
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Self-Supervised Learning | 55 | 26.96% |
| Image Classification | 15 | 7.35% |
| Object Detection | 8 | 3.92% |
| Semantic Segmentation | 8 | 3.92% |
| General Classification | 7 | 3.43% |
| Self-Supervised Image Classification | 6 | 2.94% |
| Image Retrieval | 4 | 1.96% |
| Unsupervised Pre-training | 4 | 1.96% |
| Semi-Supervised Image Classification | 4 | 1.96% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
