Question 15
Consider an input image of shape 10×10 with 3 channels of R-G-B, is processed using one of the following neural architectures:
• Fully-connected layer (FC) with 2 neurons (Note: The input volume is “flattened” into a column vector before being fed into the layer.)
• Convolutional layer (CONV) with three filters of size 2 × 2, a stride of 2 is used, and no padding is applied.
Based on the above data answer the given subquestions.
Which of the following statements is/are true about a CONV layer?
The total number of parameters depends on the depth of the input.
The total number of parameters depends on the padding.
The total number of parameters depends on the number of filters (kernel).
The total number of parameters depends on the stride.