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CapsuleNet – CapsNet – Capsule Network

 

capsnet

“A capsule is a group of neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or object part. We use the length of the activity vector to represent the probability that the entity exists and its orientation to represent the instantiation parameters. Active capsules at one level make predictions, via transformation matrices, for the instantiation parameters of higher-level capsules. When multiple predictions agree, a higher level capsule becomes active. We show that a discriminatively trained, multi-layer capsule system achieves state-of-the-art performance on MNIST and is considerably better than a convolutional net at recognizing highly overlapping digits. To achieve these results we use an iterative routing-by-agreement mechanism: A lower-level capsule prefers to send its output to higher level capsules whose activity vectors have a big scalar product with the prediction coming from the lower-level capsule.”

https://arxiv.org/abs/1710.09829

https://github.com/naturomics/CapsNet-Tensorflow

https://www.kaggle.com/kmader/capsulenet-on-mnist

https://github.com/XifengGuo/CapsNet-Keras

https://hackernoon.com/what-is-a-capsnet-or-capsule-network-2bfbe48769cc

medium.com/@culurciello/deep-neural-network-capsules-137be2877d44

https://kndrck.co/posts/capsule_networks_explained/

Matrix capsules with EM routing

View story at Medium.com

View story at Medium.com

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