A capsule is an activation vector that basically executes on its inputs some complex internal computations. Length of these activation vectors signifies the probability of availability of a feature. Furthermore, the condition of the recognized element is encoded as the direction in which the vector is pointing. In traditional, CNN uses Max pooling for invariance activities of neurons, which is nothing except a minor change in input and the neurons of output signal will remains same.
Source: Dynamic Routing Between CapsulesPaper | Code | Results | Date | Stars |
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Task | Papers | Share |
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Image Classification | 23 | 10.22% |
General Classification | 20 | 8.89% |
Classification | 18 | 8.00% |
Sentiment Analysis | 10 | 4.44% |
Semantic Segmentation | 6 | 2.67% |
Text Classification | 6 | 2.67% |
Image Segmentation | 5 | 2.22% |
Medical Image Segmentation | 4 | 1.78% |
Specificity | 4 | 1.78% |
Component | Type |
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🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |