A SENet is a convolutional neural network architecture that employs squeeze-and-excitation blocks to enable the network to perform dynamic channel-wise feature recalibration.
Source: Squeeze-and-Excitation NetworksPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
---|---|---|
Image Classification | 10 | 13.51% |
Semantic Segmentation | 7 | 9.46% |
Object Detection | 6 | 8.11% |
Classification | 5 | 6.76% |
Instance Segmentation | 4 | 5.41% |
Clustering | 2 | 2.70% |
General Classification | 2 | 2.70% |
Emotion Recognition | 2 | 2.70% |
Weather Forecasting | 1 | 1.35% |