In the context of convolutional neural networks (CNNs), what operation is used to reduce the spatial dimensions of the input volume?
- Batch Normalization
- Normalization
- Pooling
- Weight Initialization
In CNNs, 'pooling' is used to reduce the spatial dimensions of the input volume. Pooling layers downsample the feature maps, which helps in reducing computational complexity while retaining essential information, enabling the network to focus on important features.
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