Building Features from Image Data in Microsoft Azure Flashcards Preview

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Flashcards in Building Features from Image Data in Microsoft Azure Deck (10)
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1

How is the feature descriptor for scale-invariant feature transform (SIFT) structured?

8 bin histogram per keypoint

128 element vector per keypoint

36 bin histogram per keypoint

3,780 element feature vector per image

128 element vector per keypoint

2

What is a common use case for the Histogram of Ordered Gradients?

Pearson detection

Sentiment analysis

Image stitching

Image classification

Image classification

3

What term is best described as an individual measurable property or characteristic?

Feature

Activation

Descriptor

Kernel

Feature

4

If you want to detect the exact same feature in multiple images on an edge device with limited computing power, which approach would work best?

Learning

Non-hybrid

Hybrid

Non-learning

Non-learning

5

What is a learning-based approach to computer vision?

SURF

Convolutional neural network (CNN)

Object-based Resource Browser (ORB)

Ccale-invariant feature transform (SIFT)

Convolutional neural network (CNN)

6

What type of (CNN) layer reduces complexity and the risk of overfitting by downsampling the input data?

Flatten layer

Convolutional layer

Dropout layer

Pooling layer

Pooling layer

7

Which type of activation function should be used for classification tasks when more than two classes are being considered?

sigmoid

relu

tanh

softmax

softmax

8

You trained a model to 98% accuracy with a large adequate data set. When you validate the data against the test data set, it performs much worse, however. What model deficiency is likely occurring here?

High-loss variance

Underfitting

Sigmoid effect

Overfitting

Overfitting

9

What is the name for a matrix that is applied to each pixel within an image for the application of a filter or the detection of a feature?

Activation function

Kernel

Gaussian

Pool

Kernel

10

What term describes a group of images at the same scale but with different sigma values within the scale-invariant feature transform (SIFT) scale-space extrema detection step of SIFT?

Ordered gradients

Bin

Octave

Gaussian

Octave