Question 1mediummultiple choice
Full question →mediummultiple choiceObjective-mapped
A retail company wants to use Azure Computer Vision to monitor product availability on shelves. They need to detect the presence and location of any product (e.g., a box, a bottle) on a shelf image, but they do not need to identify the specific product brand or type. Which prebuilt Azure Computer Vision capability 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
Best answer
Object detection
Object detection identifies objects and their locations with bounding boxes, which directly fulfills the requirement without needing to identify the specific product type.
B
Distractor review
Image classification
Image classification assigns a label to the entire image but does not provide the location of individual objects.
C
Distractor review
Optical Character Recognition (OCR)
OCR extracts printed or handwritten text from images, not general objects.
D
Distractor review
Semantic segmentation
Semantic segmentation classifies each pixel into a predefined class (e.g., product, shelf) and typically requires a custom trained model, not a prebuilt capability.
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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Question 2
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Question 3
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Question 5
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Question 6
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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: Object detection — Object detection is the correct capability because it identifies objects in an image and provides bounding box coordinates for each detected object. This allows the company to know where each product is located on the shelf. Image classification (B) would label the entire image as containing a product or not, but would not provide location information. OCR (C) is for extracting text from images, not for detecting objects. Semantic segmentation (D) classifies each pixel into a category (e.g., shelf, product), which is more granular and typically requires custom training, not a prebuilt capability.
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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