Consider a convolutional neural network model that has three convolution layers. The first layer has 50 filters, the second layer has 100 filters, and the third layer has 200 filters. All convolution layers have stride=2, and the same padding. The input images are 300x400 pixels with RGB channels.What is the feature map size after the third convolution layer?4 points150x200x5075x100x10038x50x200

If a convolutional layer has an input size of 28x28 and applies a filter of size 3x3 with a stride of 1 and no padding, what is the size of the output feature map?

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

How many conv layers with 3x3 filters would you need to have the same receptive field as a conv layer with 11x11 filters? Assume stride=1 and no padding. Enter your answer for the number of layers as an integer, E.g., 12 points

Carefully read the source code vgg16_modified_pytorch.py . Note that this is not the standardVGG16 network, so please carefully read the source code. Answer the followingquestions:Assuming the input image size is 448 by 448,a. What is the size of the feature map before the self.fc6 layer, and how many channels doesit have?b. A key parameter has been erased. What number should replace the question mark inthe following line? Note: Assuming the input image size is 448 X 448

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?