CNN - Image Classification

Question 1: What is the primary purpose of using convolutional layers in a Convolutional Neural Network (CNN)?

• To reduce the number of parameters in the network.

• To introduce non-linearity to the model.

• To perform element-wise multiplication between input and filter.

• To capture spatial hierarchies and local patterns in data.

Question 2: What is the pooling layer in a CNN commonly used for?

• a) Increasing the spatial dimensions of the feature maps.

• b) Adding more convolutional filters to the network.

• c) Reducing the spatial dimensions of the feature maps.

• d) Converting feature maps into fully connected layers.

Q3: (a)   is the process of adjusting the weights of a neural network by analyzing the error rate from the previous iteration

Question 4 : In a CNN, what does the term "stride" refer to?

• The size of the convolutional filters.

• The number of filters in each convolutional layer.

• The amount of zero-padding added to the input.

• The step size at which the filter moves across the input.

Question5: Which layer type is commonly used to reduce the spatial dimensions of feature maps in a CNN?

• Fully connected layer

• Pooling layer

• Convolutional layer

• Activation layer

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