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

• 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

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