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Rev

Great intuitive explanation. However, one thing I don't get from your answer is why the reduction from 32x32 to 30x30 after the convolution layer. The division of pixels / pool_size ("window" size) is obvious and can't understand how I did not figured that out myself. The output of convolution layer is: IMG_HEIGHT - kernel_size + 1.

BanikPyco
– BanikPyco

2024-01-14 13:52:20 +00:00
Commented Jan 14, 2024 at 13:52
1

Its been a long time since ive done this, so bear with me: If e.g. your base is 4x4, and your convolution layer is 3x3. Try drawing the different positions you can put your conv layer on top of the 4x4 base layer. There are 4 positions if im right. So your output of this operations are a 2x2 new layer. In other words, the convolution operation decreased the size of the base layer. A similar thing happens in my above example.

charelf
– charelf

2024-01-15 10:30:29 +00:00
Commented Jan 15, 2024 at 10:30
1

i.postimg.cc/L5qTXTfP/image.jpg

charelf
– charelf

2024-01-15 10:34:59 +00:00
Commented Jan 15, 2024 at 10:34

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