CNNs · Level 2 of 5
Global Average Pooling
Averaging each feature channel over all spatial positions.
It converts spatial feature maps into a per-channel summary.
Example
A classifier receives one number per final feature channel.
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Audio transcript
Global Average Pooling. Averaging each feature channel over all spatial positions. It converts spatial feature maps into a per-channel summary. For example: A classifier receives one number per final feature channel.
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Why it matters
This helps you interpret feature shapes and spatial behavior in image networks.
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Quick recall question
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