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DeepLearning_GPT3_questions

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Pytanie 73
Which operation is used in UNet to recover the image resolution?
Upsampling
Pooling
Convolution
Dropout
Pytanie 74
Which part of UNet captures the context of an image?
The bottleneck layer
All of the above
The contracting path
The expansive path
Pytanie 75
What type of deep learning task is UNet commonly used for?
Natural language processing
Image segmentation
Image classification
Object detection
Pytanie 76
Which of the following is an application of autoencoders?
Dimensionality reduction
Anomaly detection
All of the above
Image denoising
Pytanie 77
What is the difference between a denoising autoencoder and a standard autoencoder?
Denoising autoencoders use noisy data as input during training.
Denoising autoencoders have an additional noise reduction layer.
Denoising autoencoders use a different activation function.
Denoising autoencoders use a different cost function.
Pytanie 78
What is the bottleneck layer in an autoencoder?
The first hidden layer in the decoder network.
The last hidden layer in the decoder network.
The first hidden layer in the encoder network.
The last hidden layer in the encoder network.
Pytanie 79
Which of the following is a type of regularized autoencoder?
All of the above
Denoising autoencoder
Contractive autoencoder
Sparse autoencoder
Pytanie 80
What is the objective of a variational autoencoder (VAE)?
To minimize the distance between the true data distribution and the learned distribution.
To minimize the reconstruction error between the input and the output.
To maximize the likelihood of the data under the encoder distribution.
To maximize the lower bound on the log-likelihood of the data.
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