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What is Dynamic Routing in Capsule Networks about?

Dynamic routing between capsules is proposed as an improvement over convolutional neural networks. Capsules represent entities with vectors, where the vector length indicates probability of existence and orientation represents properties. An iterative routing process sends capsule outputs to appropriate parent capsules in the next layer. This "routing by agreement" allows explaining away of overlapping objects better than max pooling. The model achieves state-of-the-art performance on MNIST and outperforms

Author

gheorghe gardu

Language

EN