https://marovi.ai/index.php?action=history&feed=atom&title=Translations%3ABatch_Normalization_Accelerating_Deep_Network_Training%2F16%2FenTranslations:Batch Normalization Accelerating Deep Network Training/16/en - Revision history2026-04-28T03:23:40ZRevision history for this page on the wikiMediaWiki 1.39.1https://marovi.ai/index.php?title=Translations:Batch_Normalization_Accelerating_Deep_Network_Training/16/en&diff=13722&oldid=prevFuzzyBot: Importing a new version from external source2026-04-27T21:40:19Z<p>Importing a new version from external source</p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 21:40, 27 April 2026</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><del style="font-weight: bold; text-decoration: none;">Batch </del>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.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">{{Term|batch </ins>normalization<ins style="font-weight: bold; text-decoration: none;">}} </ins>is typically applied before the <ins style="font-weight: bold; text-decoration: none;">{{Term|</ins>activation function<ins style="font-weight: bold; text-decoration: none;">}}</ins>, after the linear or convolutional transformation. When used with <ins style="font-weight: bold; text-decoration: none;">{{Term|convolution|</ins>convolutional layers<ins style="font-weight: bold; text-decoration: none;">}}</ins>, the normalization is performed per feature map (channel) rather than per individual <ins style="font-weight: bold; text-decoration: none;">{{Term|</ins>activation <ins style="font-weight: bold; text-decoration: none;">function|activation}}</ins>, sharing statistics across all spatial locations within a feature map.</div></td></tr>
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</table>FuzzyBothttps://marovi.ai/index.php?title=Translations:Batch_Normalization_Accelerating_Deep_Network_Training/16/en&diff=3042&oldid=prevFuzzyBot: Importing a new version from external source2026-04-27T00:31:31Z<p>Importing a new version from external source</p>
<p><b>New page</b></p><div>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.</div>FuzzyBot