Convolutional Neural Networks
AmoebaNet
Introduced by Real et al. in Regularized Evolution for Image Classifier Architecture SearchAmoebaNet is a convolutional neural network found through regularized evolution architecture search. The search space is NASNet, which specifies a space of image classifiers with a fixed outer structure: a feed-forward stack of Inception-like modules called cells. The discovered architecture is shown to the right.
Source: Regularized Evolution for Image Classifier Architecture Search
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Image Classification | 4 | 17.39% |
| Object Detection | 4 | 17.39% |
| Keypoint Detection | 2 | 8.70% |
| Semantic Segmentation | 2 | 8.70% |
| Object | 2 | 8.70% |
| Graph Neural Network | 1 | 4.35% |
| Image Augmentation | 1 | 4.35% |
| Robust Object Detection | 1 | 4.35% |
| Real-Time Object Detection | 1 | 4.35% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
Average Pooling
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Pooling Operations | |
Convolution
|
Convolutions | |
Max Pooling
|
Pooling Operations | |
Softmax
|
Output Functions | |
Spatially Separable Convolution
|
Convolutions |
