Nauka
DeepLearning_GPT3_questions
Wyświetlane są wszystkie pytania.
Pytanie 81
Which of the following pooling methods is designed to capture spatial context in the feature maps?
Average pooling
Max pooling
Spatial pyramid pooling
Global pooling
Pytanie 82
What is the main disadvantage of using pooling layers in convolutional neural networks?
They can lead to overfitting
They can reduce the representational capacity of the model
They can make the model more computationally expensive
They can increase the size of the output volume
Pytanie 83
Which of the following statements about max pooling is true?
) It can be used as an alternative to fully connected layers
It can be used to learn translation invariance
It performs the same operation on all feature maps in a given layer
It always produces a smaller output volume than the input volume
Pytanie 84
Which of the following pooling methods does not involve any parameter learning?
Max pooling
Average pooling
L2 pooling
Global pooling
Pytanie 85
What is the purpose of pooling layers in convolutional neural networks?
To increase the size of the feature maps
To add non-linearities to the model
To reduce the spatial dimensions of the output volume
To increase the number of parameters in the model