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Convolutional neural network: Difference between revisions
→Padding
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Convolutional layers yield an output smaller than the input size. | Convolutional layers yield an output smaller than the input size. | ||
We can use padding to increase the input size. | We can use padding to increase the input size. | ||
See [https://www.machinecurve.com/index.php/2020/02/10/using-constant-padding-reflection-padding-and-replication-padding-with-keras/ Machinecurve: Using Constant Padding, Reflection Padding and Replication Padding with Keras] | |||
;Types of padding | ;Types of padding | ||
* Zero | * Zero/Constant | ||
* Mirror | * Mirror/Reflection | ||
* Replication | |||
With convolution layers in tensorflow and other libraries you often see these two types of padding: | With convolution layers in tensorflow and other libraries you often see these two types of padding: | ||