Question

Consider a CNN that takes in 32 × 32 grayscale images and has a single convolution layer with three 5 × 5 convolution filters (without boundary padding).

How many parameters are in this model?

Answer 1

The CNN model with a single convolution layer with three 5x5 filters for 32x32 grayscale images without padding has a total of 78 parameters.

Step-by-step explanation:

The student's question relates to the calculation of the number of parameters in a Convolutional Neural Network (CNN) model that takes in 32 × 32 grayscale images with a single convolution layer comprising three 5 × 5 convolution filters without boundary padding. Given that grayscale images have only one channel, each filter will have 5 × 5 parameters corresponding to the weights of the connections plus a bias term. Since there are three filters, the total number of parameters for each filter is 5 × 5 + 1 = 26. Multiplying this by the number of filters gives the total number of parameters in the model, which is 3 × 26 = 78.