Convolutional Neural Networks

Which one is a non-linear activation function?

For an image recognition problem, which neural network architecture would be better suited to solve the problem?

Ten neurons in the hidden layer and five neurons in the output layer; how many weights and biases parameters?

Given an image of size 27 x 27 and a filter of size 5 x 5 with a stride of 2 and no padding. What is the output size?

RGB image size = 64 x 64 x 3, 10 filters, each of shape 5 x 5 x 3 with stride 1 and pad 2. What is the output size?

Input size = 27 x 27, filter size = 7 x 7, stride = 1. How many layers of zeros are added on each side so that the output size remains 27 x 27?

                 _____ produces a discrete probability distribution vector.

RGB image size = 32 x 32 x 3, 10 filters, each of shape 5 x 5 x 3 with stride 1 and pad 0. How many weights and biases for the convolutional operation?

Given the shown input matrix of shape 4 x 4. What will be the output on applying a max pooling of size 2 x 2 with a stride of 2?

What value would be in place of the question mark?