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GitHub-Copilot real exams

Exam Code: GitHub-Copilot

Exam Name: GitHub CopilotCertification Exam

Version: V13.25

Q & A: 72 Questions and Answers

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NEW QUESTION: 1

A. Option E
B. Option A
C. Option D
D. Option B
E. Option C
Answer: B

NEW QUESTION: 2
Where should a user create new Camera Raw metadata properties?
A. Right-click on an imported file in the Project panel> Add properties
B. Right-click on an imported file in the Project panel> Modify properties
C. Metadata window, select the panel menu> Metadata Display, then Add Property
D. Window > Projects > Metadata display> Modify properties
Answer: C

NEW QUESTION: 3
You need to determine the location of cars in an image so that you can estimate the distance between the cars.
Which type of computer vision should you use?
A. optical character recognition (OCR)
B. image classification
C. object detection
D. face detection
Answer: C
Explanation:
Explanation
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like
"indoor", which can't be localized with bounding boxes.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

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