Quiz
Module 13 Review
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Fragen in diesem Quiz (14)
1Residual layers sum the information, and it results in a ______ network
- Athinner
- Bsimple
- Cfatter
- Dcomplex
2Concatenation layer combines multiple inputs by concatenating making the network _____.
- Afatter
- Bthinner
- Ccomplex
- Dsimple
3____ require fewer parameters than a fully connected layer
because the parameters are shared across columns thereby improving
computation efficiency- AConvolution layers
- BPooling layers
- CInput layers
- DFully connected layers
4_____ retains information that would otherwise be disregarded
- Apadding
- Bpooling
- CFully connected layer
- DOutput layer
5 The dimension of a feature map is determined by the input dimension, padding dimension, filter dimension and the _______.
- Astride
- BOutput dimension
- CPooling dimension
- DHorizontal dimension
6When using CNN for image classification, the _______ layer is useful when you want to check if a particular object exists in an image, more than its position.
- Apooling
- Bpadding
- Cinput
- Doutput
7 Which one of the following statements is not true about skip layers?
- AAdding a skip layer helps the network remember latent features that it may have learned early
- BSkip layers help mitigate the vanishing gradient problem.
- CA skip layer is handled through two types of layers: concatenation layers and residual layers
- DSkip layers are introduced to solve the problem of bottlenecking
8In CNN, width, height, and stride are all examples of ________.
- AHyperparameters
- BLearning parameters
- CWeights
- DFeature maps
9A______ is a stage of feature extraction that consists of multiple convolutions that are usually stacked then combined with a concatenation layer or a residual layer
- AFilter
- BBlock
- CHidden layer
- DSkip layer
10For CNN, grayscale images require ___ channel(s) while color images need ___ channel(s)
- A1, 3
- B2, 3
- C1, 4
- D2, 4
11Which of the following about filters is not true?
- AEach filter creates non-equivariant representations of the input to optimize learning
- BFilters have weights
- CFilters have a bias term
- DThe parameters in each filter are shared by multiple columns in the data.
12Which localized summary can a pooling layer provide?
- AAverage, minimum, and maximum summaries
- BOnly minimum and maximum summaries
- COnly average summary
- DNone, summaries are only done with filters, not pooling layers
13Which statements is not true about cardinality?
- AIt is the number of blocks within a transformation set.
- BIt can be expensive to train.
- CIt is an alternative to going deeper or wider for increased accuracy.
- DIf skip layers are used, residual connections are recommended to reduce training cost.
14Which of these is not a reasonable padding rule?
- AIf the stride is 2, the output image size is double the input image size.
- BPadding is added first to the right side then the left.
- CImages are padded with zeros.
- DThe horizontal and vertical padding sizes are independent of each other.
Informationen
- Beschreibung
- Quiz am Module 13 Review, erstellt von Nick Feldman am 01/05/2022.
- Autor
- Nick Feldman
- Sprache
- English
- Aufrufe
- 1
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