Nauka

DeepLearning_GPT3_questions

Wyświetlane są wszystkie pytania.
Pytanie 73
Which operation is used in UNet to recover the image resolution?
Pooling
Upsampling
Convolution
Dropout
Pytanie 74
Which part of UNet captures the context of an image?
The contracting path
The expansive path
All of the above
The bottleneck layer
Pytanie 75
What type of deep learning task is UNet commonly used for?
Object detection
Image segmentation
Image classification
Natural language processing
Pytanie 76
Which of the following is an application of autoencoders?
Dimensionality reduction
All of the above
Image denoising
Anomaly detection
Pytanie 77
What is the difference between a denoising autoencoder and a standard autoencoder?
Denoising autoencoders use a different activation function.
Denoising autoencoders have an additional noise reduction layer.
Denoising autoencoders use a different cost function.
Denoising autoencoders use noisy data as input during training.
Pytanie 78
What is the bottleneck layer in an autoencoder?
The last hidden layer in the decoder network.
The first 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 reconstruction error between the input and the output.
To maximize the lower bound on the log-likelihood of the data.
To maximize the likelihood of the data under the encoder distribution.
To minimize the distance between the true data distribution and the learned distribution.
Przejdź na Memorizer+
W trybie nauki zyskasz:
Brak reklam
Quiz powtórkowy - pozwoli Ci opanować pytania, których nie umiesz
Więcej pytań na stronie testu
Wybór pytań do ponownego rozwiązania
Trzy razy bardziej pojemną historię aktywności
Wykup dostęp