Translations:Batch Normalization Accelerating Deep Network Training/16/en: Difference between revisions

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Message definition (Batch Normalization Accelerating Deep Network Training)

{{Term|batch normalization}} is typically applied before the {{Term|activation function}}, after the linear or convolutional transformation. When used with {{Term|convolution|convolutional layers}}, the normalization is performed per feature map (channel) rather than per individual {{Term|activation function|activation}}, sharing statistics across all spatial locations within a feature map.

batch normalization is typically applied before the activation function, after the linear or convolutional transformation. When used with convolutional layers, the normalization is performed per feature map (channel) rather than per individual activation, sharing statistics across all spatial locations within a feature map.

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	~~Batch~~ normalization is typically applied before the activation function, after the linear or convolutional transformation. When used with convolutional layers, the normalization is performed per feature map (channel) rather than per individual activation, sharing statistics across all spatial locations within a feature map.		{{Term\|batch normalization}} is typically applied before the {{Term\|activation function}}, after the linear or convolutional transformation. When used with {{Term\|convolution\|convolutional layers}}, the normalization is performed per feature map (channel) rather than per individual {{Term\|activation function\|activation}}, sharing statistics across all spatial locations within a feature map.