Suppose your input is a 300*300 color (RGB) image, and you are not using a convolutional network. If the first hidden layer has 100 neurons, each one fully connected to the input, how many parameters does this hidden layer have (assume each neuron has its own bias parameter)?       a.9,000,001b. 27,000,001c.27,000,100d.9,000,100

Suppose your input is a 300*300 color (RGB) image, and you use a convolutional layer with 100 filters that are each 5×5. How many parameters does this hidden layer have (assume each filter has its own bias parameter)?a.2600b.7600c.2501d.7500

Figure QA1 is a small convolutional neural network that converts a 15x15 image into4 output values. The network has the following layers and operations from input tooutput: convolution with 3 filters, max pooling, ReLu, and finally a fully-connectedlayer. For this network we will not be using any bias to set parameters (b).Fig. QA1(a) How many weights in the convolutional layer do we need to learn

What is the number of parameters in an RNN's hidden layer if each cell connects to 200 other cells and includes a bias term, with a total of 100 cells in the layer?Question 10Answera.20100b.20000c.100d.200

In a Fully Connected NN, if the input volume is 32x32x3 connected to a singlelayer of 5 neurons, how many parameters must be learned?

In a CNN, if we have a 32x32x3 input volume followed by four layers of 3x3x3filters with stride = 1 and pad = 0, how many parameters must be learned?(a) 4(b) 27(c) 28(d) 108(e) 112