Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
A manufacturing company uses Azure Computer Vision to analyze assembly line images. They need to identify specific product defects (e.g., scratches, dents) and also read serial numbers printed on the products in various fonts. Which combination of Azure Computer Vision features should they use?
Answer choices
Why each option matters
Good practice is not just finding the correct option. The wrong answers often show the exact trap the exam wants you to fall into.
A
Distractor review
Image Analysis (object detection) and OCR
Prebuilt object detection in Image Analysis can detect common objects but is not trained for specific product defects like scratches or dents.
B
Best answer
Custom Vision (object detection) and OCR
Custom Vision object detection can be trained to identify and locate defects, while OCR reads the serial numbers. This combination solves both tasks effectively.
C
Distractor review
Face API and OCR
Face API is designed for human faces, not product defects. OCR could read text but the defect detection requirement is unaddressed.
D
Distractor review
Image Analysis (tags) and OCR
Image Analysis tags provide labels for the entire image without localization. Defect detection requires pinpointing where the defect is, which tags cannot do.
Common exam trap
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Technical deep dive
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Related practice questions
Related AI-900 practice-question pages
Use these pages to review the topic behind this question. This is how one missed question becomes focused revision.
More questions from this exam
Keep practising from the same exam bank, or move into a focused topic page if this question exposed a weak area.
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FAQ
Questions learners often ask
What does this AI-900 question test?
Static NAT maps one inside address to one outside address.
What is the correct answer to this question?
The correct answer is: Custom Vision (object detection) and OCR — Custom Vision allows training a custom object detection model to recognize and locate specific defects (like scratches and dents) that are not covered by predefined models. Optical Character Recognition (OCR) via the Read API is designed to extract printed text from images, including serial numbers in different fonts. The combination of Custom Vision object detection and OCR directly addresses both requirements. Prebuilt Image Analysis may not detect company-specific defects. Face API is irrelevant. Tags alone do not provide localization.
What should I do if I get this AI-900 question wrong?
Then try more questions from the same exam bank and focus on understanding why the wrong options are tempting.
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