Test: DeepLearning_GPT3

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DeepLearning_GPT3_questions

Pytanie 81

Which of the following pooling methods is designed to capture spatial context in the feature maps?

Global pooling

Spatial pyramid pooling

Max pooling

Average pooling

Pytanie 82

What is the main disadvantage of using pooling layers in convolutional neural networks?

They can reduce the representational capacity of the model

They can lead to overfitting

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?

Average pooling

Global pooling

Max pooling

L2 pooling

Pytanie 85

What is the purpose of pooling layers in convolutional neural networks?

To increase the number of parameters in the model

To reduce the spatial dimensions of the output volume

To increase the size of the feature maps

To add non-linearities to the model