Data Science and Machine Learning (Theory and Projects) A to Z - Yolo: Yolo Training Data Generation

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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 limitation of using a target vector for object localization in images?
It can only handle images with multiple objects.
It is not compatible with YOLO.
It requires a high-resolution image.
It can only localize one object per image.
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How does YOLO handle multiple objects in an image?
By using a single bounding box for all objects.
By dividing the image into a grid of cells.
By ignoring overlapping objects.
By increasing the image resolution.
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What assumption is made about each cell in YOLO's grid?
Each cell is empty.
Each cell contains multiple objects.
Each cell overlaps with adjacent cells.
Each cell is treated as a standalone image.
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How are the centers of bounding boxes represented in YOLO's training data?
As absolute pixel coordinates.
As a percentage of the image size.
As relative coordinates within a cell.
As a fixed point in the image.
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the range for the BX and BY values in YOLO's labeling system?
Between 0 and 10.
Between 0 and 1.
Between 1 and 100.
Between -1 and 1.
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What challenge arises when multiple objects have their centers in the same cell?
The objects are ignored.
The grid cells become overlapping.
The image resolution is too low.
The CNN can only output one bounding box.
7.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What concept will be introduced in the next video to address overlapping objects?
Anchor boxes.
Larger grid cells.
Higher resolution images.
Single bounding box strategy.
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