Convolutional Neural Networks
VGG-16
Introduced by Simonyan et al. in Very Deep Convolutional Networks for Large-Scale Image Recognition
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| General Classification | 28 | 10.11% |
| Image Classification | 26 | 9.39% |
| Object Detection | 23 | 8.30% |
| Model Compression | 19 | 6.86% |
| Quantization | 14 | 5.05% |
| Semantic Segmentation | 13 | 4.69% |
| Network Pruning | 12 | 4.33% |
| Neural Network Compression | 7 | 2.53% |
| Object Recognition | 6 | 2.17% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |