A novel built-in attention mechanism, that is complementary to all other prior attention mechanisms (e.g. squeeze and excitation, transformers) that are external (i.e., not built-in - please read paper for more details)
Source: Weight Excitation: Built-in Attention Mechanisms in Convolutional Neural NetworksPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Computed Tomography (CT) | 1 | 6.67% |
Lung Nodule Detection | 1 | 6.67% |
Lung Nodule Segmentation | 1 | 6.67% |
3D Action Recognition | 1 | 6.67% |
3D Classification | 1 | 6.67% |
3D Object Classification | 1 | 6.67% |
3D Semantic Segmentation | 1 | 6.67% |
Action Detection | 1 | 6.67% |
Action Recognition | 1 | 6.67% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |