Parameters to train, common settings

With parameter sharing, the convolution involves thus for each filter $F\times F\times D_1$ weights plus one bias parameter.

In total we have

$$\left(F\times F\times D_1\right) \times K+K_{\mathrm{biases}},$$

parameters to train by back propagation.

It is common to let $K$ come in powers of $2$, that is $32$, $64$, $128$ etc.

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