Swag (#70)

* abstract

* Add style cleanup

* Extra swag

* Sacv

* aishent

sections/convolutional neural networks/subsampling/poolers.tex

@@ -1,6 +1,5 @@
 Despite the kernels doing a great job at making the image smaller, the resulting data is still quite too big to work with.  
 For that reason one can use poolers, which are nothing but dull compression algorithms.
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 The most used pooler is the max pooler. \cite{Graham2014}  \\
 This simple unit traditionally takes four adjacent pixels, then determines the darkest one, and simply concatenates the four original pixels into this smaller single one.  
 Repeat this process over the whole image, and you just scaled it to one fourth of it's original size.