net $=$ googlenet;

layers $=$ net.Layers;

conv $=$ layers$(2)$

conv $=$

Convolution$2$DLayer with properties:

Name: 'conv$1-7$x$7\_$s$2\text{'}$

Hyperparameters

FilterSize: $[77]$

NumChannels: $3$

NumFilters: $64$

Stride: $[22]$

DilationFactor: $[11]$

PaddingMode: 'manual'

PaddingSize: $[3333]$

Learnable Parameters

Weights: $[7$x$7$x$3$x$64$ single$]$

Bias: $[1$x$1$x$64$ single$]$

Given the information on the convolution layer shown, please select all the following

statements that are true

$-$The total number of weights is $9408,$

$-$As it moves over the image, it will jump over a pixel each time

$-$The convolution is $2$ dimensional and covers a $7$x$7$ pixel range

$-$the total number of weights is $147$

$-$the total number of biases is $64$

$-$The convolution is designed for black and white images

$-$The padding is selected such that it$$ makes the center of the filter start on the first pixel on each row$/$column

$-$The padding reduces the size of the filter from $7$x$7$ to a $4$x$4$

$-$The three channels of the convolution correspond to red$/$green$/$blue color channels

$-$the total number of biases is $9472$