stem/AI/Neural Networks/CNN/Max Pooling.md

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- Maximum within window and writes result to output
- Downsamples image
- More non-linearity
- Doesn't remove important information
- Max value is the good bit
- No parameters
![[max-pooling.png]]
## Design Parameters
- Size of input image
- 252 x 252 x 1 x n
- Padding
- Kernel size
- 3 x 3 x 1
- Doesn't need to be odd
- 2 x 2
- Stride
- Typically n
- For n x n kernel size
- Sometimes 4 x 4 in early layers
- 16 times less data
- Rapid downsample
- Size of computable output
- 250 x 250 x 1 x n
- Depends on padding and striding