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Home Neural Networks

Batch Normalization, Instance Normalization, Layer Normalization: Structural Nuances

August 11, 2020
in Neural Networks
Batch Normalization, Instance Normalization, Layer Normalization: Structural Nuances
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Let us establish some notations, that will make the rest of the content, easy to follow. We assume that the activations at any layer would be of the dimensions NxCxHxW (and, of course, in the real number space), where, N = Batch Size, C = Number of Channels (filters) in that layer, H = Height of each activation map, W = Width of each activation map.

Feature Map Dimensions

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Generally, normalization of activations require shifting and scaling the activations by mean and standard deviation respectively. Batch Normalization, Instance Normalization and Layer Normalization differ in the manner these statistics are calculated.

Normalization

Credit: BecomingHuman By: Mayank Agarwal

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