Question 1hardmultiple choice
Full question →hardmultiple choiceObjective-mapped
An autonomous vehicle system needs to both read the speed limit text on traffic signs and detect the presence and location of pedestrians crossing the road. Which combination of Azure Computer Vision capabilities should be used?
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 Classification and OCR
Image classifies the entire scene but does not provide location of objects; OCR reads text. This combination lacks object detection for pedestrians.
B
Distractor review
Semantic Segmentation and OCR
Semantic segmentation provides pixel-level classification but is not designed to read text; OCR covers text reading, but pedestrian detection is better handled by object detection for bounding boxes.
C
Best answer
Optical Character Recognition (OCR) and Object Detection
OCR reads text from signs, and object detection finds and locates pedestrians, which together meet both requirements.
D
Distractor review
Face Detection and OCR
Face detection finds only faces, not all pedestrians, and cannot detect a pedestrian from behind or without a visible face.
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: Optical Character Recognition (OCR) and Object Detection — Optical Character Recognition (OCR) extracts text from images, enabling the vehicle to read speed limit numbers. Object Detection identifies and locates multiple objects (like pedestrians) within an image using bounding boxes. Image Classification (A) only labels the whole image. Semantic Segmentation (B) classifies each pixel but does not read text. Face Detection (D) is a specific type of object detection but not for general objects or text.
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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