Data Science and Machine Learning (Theory and Projects) A to Z - Yolo: Yolo Anchor Boxes

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Information Technology (IT), Architecture, Physics, Science
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University
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Hard
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7 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the primary purpose of labeling training data in object detection?
To identify the color of objects
To define target vectors for each object
To determine the size of the image
To enhance image resolution
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How are target vectors structured for each cell in an image grid?
As a color-coded matrix
As a one-hot encoded vector
As a binary vector with multiple ones
As a single number
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
Which aspect of YOLO is responsible for generating multiple targets for each cell?
The use of anchor boxes
The image resolution
The labeling of training data
The convolutional neural network
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the role of anchor boxes in the YOLO algorithm?
To categorize objects based on color
To increase the image size
To handle multiple objects in a single cell
To reduce the number of cells in an image
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does the number of anchor boxes affect the target vector length?
It decreases the length
It increases the length proportionally
It has no effect
It doubles the length
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What type of loss function is typically used for class categories in YOLO?
Mean squared error
Cross entropy
Hinge loss
Absolute error
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What future topic is hinted at in the discussion of YOLO's mechanics?
Image enhancement
Non-maximum suppression
Color correction
Data augmentation
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