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Convolutional neural network: Difference between revisions
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and the following 3x3 kernel:<br> | and the following 3x3 kernel:<br> | ||
<pre> | |||
1 1 1 | |||
2 1 2 | |||
3 2 1 | |||
</pre> | |||
For each possible position of the 3x3 kernel over the input image, | For each possible position of the 3x3 kernel over the input image, | ||
we perform an element-wise multiplication (<math>\odot</math>) and sum over all entries to get a single value. | we perform an element-wise multiplication (<math>\odot</math>) and sum over all entries to get a single value.<br> | ||
Placing the kernel in the first position would yield:\\ | |||
<math> | |||
\begin{bmatrix} | |||
1 & 2 & 3\\ | |||
6 & 7 & 8\\ | |||
2 & 5 & 9 | |||
\end{bmatrix} | |||
\odot | |||
\begin{bmatrix} | |||
1 & 1 & 1\\ | |||
2 & 1 & 2\\ | |||
3 & 2 & 1 | |||
\end{bmatrix} | |||
= | |||
\begin{bmatrix} | |||
1 & 2 & 3\\ | |||
12 & 7 & 16\\ | |||
6 & 10 & 9 | |||
\end{bmatrix} | |||
</math>\\ | |||
Summing up all the elements gives us <math>66</math> which would go in the first index of the output. | |||
===Stride=== | ===Stride=== | ||