$11.$ Given a CNN classifier defined by the layers in the left column of Table Q$11.$ For each layer, calculate the activation map dimensions and the number of parameters.

Notation:

$$ Conv$-$K$-$N denotes a convolutional layer with N filters, each them of size K$\backslash$times K$.$

Padding and stride parameters are always $0$ and $1$ respectively.

$$ Pool$-$K indicates a K$\backslash$times K pooling layer with stride K and padding $0.$

$$ FC$-$N stands for a fully$-$connected layer with N neurons.

Layer

Input Conv$-9-32$ Pool$-2$ Conv$-5-64$ Pool$-2$ FC$-5$

Table Q$11$

Activation map dimensions

$128\backslash$times $128\backslash$times $3$

Number of parameters

$0$