Convolutional Neural Network Quiz

You have an input volume that is 63x63x16, and convolve it with 32 filters that are each 7x7, using a stride of 2 and no padding. What is the output volume?

• 16x16x32

• 29x29x16

• 29x29x32

• 16x16x16

You have an input volume that is 15x15x8, and pad it using “pad=2.” What is the dimension of the resulting volume (after padding)?

• 19x19x12

• 17x17x10

• 19x19x8

• 17x17x8

The most suitable activation function for hidden layer

• Sigmoid

• Softmax

• ReLu

• tanh

What is a convolutional neural network (CNN) and how is it different from a regular neural network?

• CNN is designed for processing text data, while regular neural network is designed for processing visual data.

• CNN uses convolutional layers to process visual data, while regular neural network does not.

• CNN has fewer parameters than regular neural network, making it less powerful.

• CNN uses only fully connected layers, while regular neural network uses convolutional layers.

Explain the concept of convolution in the context of CNNs.

• Applying a filter to an input to produce a feature map

• Multiplying two matrices together

• Adding all the elements of a matrix

• Finding the maximum value in a matrix

What is the purpose of using pooling layers in a CNN?

• To add noise to the data and reduce model performance

• To increase spatial dimensions and encourage overfitting

• To make the model more complex and difficult to train

• To reduce spatial dimensions and control overfitting

Describe the role of activation functions in a CNN.

• Activation functions introduce non-linearity into the network

• Activation functions are only used in fully connected layers of the CNN

• Activation functions are used to initialize the weights of the CNN

• Activation functions help in reducing the dimensionality of the input data

Explain the concept of feature maps in the context of CNNs.

• The size of the input image

• The color palette used in an image

• The output of applying a filter to an input image

• The number of layers in a CNN

What is the role of padding in CNNs and why is it used?

• It is used to preserve the spatial dimensions of the input as it passes through the layers of the network.

• It is used to reduce the spatial dimensions of the input

• It is used to increase the computational complexity of the network

• It is used to add noise to the input data

What are some common applications of convolutional neural networks?

• Image recognition, object detection, facial recognition, medical image analysis, and video analysis

• Cooking recipes, travel planning, and book recommendations

• Music composition, sports analysis, and social media monitoring

• Weather forecasting, stock market analysis, and language translation