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Convolutional neural network: Difference between revisions
→Convolutions
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Summing up all the elements gives us <math>66</math> which would go in the first index of the output. | Summing up all the elements gives us <math>66</math> which would go in the first index of the output. | ||
The formula for the output resolution of a convolution is: | |||
<math> | |||
\frac{x-k+2p}{s}+1 | |||
</math> | |||
where: | |||
* \(x\) is the input resolution | |||
* \(k\) is the kernel size (e.g. 3) | |||
* \(p\) is the padding on each side | |||
* \(s\) is the stride | |||
Typically a \(3 \times 3\) conv layer will have a padding of 1 and stride of 1 to maintain the same size. A stride of \(2\) would halve the resolution. | |||
===Stride=== | ===Stride=== | ||