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

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

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

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

Suppose we have the following convolutional neural network architecture:Input volume: 15x15x1 (i.e. width = 15, height = 15, and depth = 1)First convolutional layer: 5 filters, with receptive field 3x3x1Second convolutional layer: 5 filters, with receptive field 2x2x5Output layer: fully connected with 10 neurons.How many weights are there in each layer?

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