Convolutional Neural Networks QUIZ - MCQ QUESTIONS AND ANSWERS

Question: 1

What is the primary advantage of using pre-trained CNN models?

Question: 2

How do dropout layers contribute to training CNNs?

Question: 3

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

Question: 4

Which type of pooling operation selects the maximum value from each region?

Question: 5

What is the purpose of the dropout technique in CNNs?

Question: 6

What is the purpose of the padding technique in CNNs?

Question: 7

What is the primary function of the Softmax activation function?

Question: 8

Which layer type helps reduce overfitting in a CNN?

Question: 9

What role do convolutional layers play in CNNs?

Question: 10

Which activation function is often used in hidden layers of CNNs?

Question: 11

What is the primary purpose of pooling layers in CNNs?

Question: 12

What is the primary objective of using batch normalization in CNNs?

Question: 13

Which layer in a CNN is responsible for introducing non-linearity into the model?

Question: 14

In the context of CNNs, what is the purpose of the "padding" technique?

Question: 15

What role do fully connected layers play in a CNN?

Question: 16

What is the primary advantage of using Convolutional Neural Networks (CNNs) over Artificial Neural Networks (ANNs) for computer vision tasks?

Question: 17

How does data augmentation contribute to improving CNN performance?

Question: 18

Which activation function is commonly used in the output layer of a CNN for multi-class classification tasks?

Question: 19

In a CNN architecture, what does the term "kernel" refer to?

Question: 20

Which type of layer in a CNN helps the model reduce the spatial dimensions of feature maps by selecting the maximum values within specific regions?

Question: 21

What is the primary advantage of using convolutional layers in CNNs for image processing tasks?

Question: 22

In the context of CNNs, what does "stride" refer to?

Question: 23

Which layer in a CNN is responsible for producing the final prediction or classification of input data?

Question: 24

What is the primary objective of using dropout in a CNN?

Question: 25

What type of CNN layer is used to detect features from input images or sequences adaptively?

Question: 26

Which layer is responsible for converting the 2-dimensional feature maps into a 1-dimensional vector in a CNN?

Question: 27

What is the purpose of Batch Normalization in a CNN?

Question: 28

Which activation function is commonly used in the hidden layers of a CNN?

Question: 29

What is the purpose of the "padding" hyperparameter in a convolutional layer?

Question: 30

Which layer in a CNN is responsible for reducing the spatial dimensions of feature maps and decreasing the number of parameters?