- A
OCR (Read API) and Object Detection
Correct. OCR extracts text from images, even when rotated or skewed. Object Detection identifies and locates specific objects (like a 'FRAGILE' sticker) within the image.
- B
Image Classification and OCR (Read API)
Why wrong: Incorrect. Image Classification can classify the entire image but does not provide location information for the sticker. The scenario requires detecting the sticker's presence, which Object Detection does better.
- C
Object Detection and Face Detection
Why wrong: Incorrect. While Object Detection can locate the sticker, Face Detection is designed for human faces and is not useful for reading labels or detecting stickers. OCR is needed for text.
- D
Image Classification and Face Detection
Why wrong: Incorrect. Neither capability addresses the need to read rotated text (OCR is needed) nor does Face Detection help with sticker detection.
Quick Answer
The answer is the combination of OCR (Read API) and Object Detection. This pairing is correct because the Read API is specifically designed to extract printed and handwritten text from images, handling rotated or skewed text automatically, while Object Detection identifies and locates specific objects within an image—in this case, a 'FRAGILE' sticker. On the Microsoft Azure AI Fundamentals AI-900 exam, this scenario tests your ability to match Azure Computer Vision capabilities to real-world tasks, often appearing as a multi-condition question where each requirement maps to a distinct service. A common trap is confusing the Read API with Optical Character Recognition (OCR) in general, but remember that the Read API is the optimized, cloud-based version for skewed text, whereas Object Detection is for locating objects, not just reading labels. Memory tip: Think "Read for text, Detect for objects"—if you need to both read a label and find a sticker, you need both.
AI-900 Practice Question: Describe features of computer vision workloads on Azure
This AI-900 practice question tests your understanding of describe features of computer vision workloads on azure. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A logistics company processes packages on an automated conveyor belt. They need to read shipping labels that are often rotated or skewed, and also detect whether a 'FRAGILE' sticker is present on the package. Which combination of Azure Computer Vision capabilities should they use?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
OCR (Read API) and Object Detection
The scenario requires reading rotated or skewed text from shipping labels (handled by the OCR Read API, which extracts printed and handwritten text from images, even when rotated or skewed) and detecting whether a 'FRAGILE' sticker is present (handled by Object Detection, which identifies and locates specific objects—like stickers—within an image). Option A correctly pairs these two capabilities to meet both requirements.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
OCR (Read API) and Object Detection
Why this is correct
Correct. OCR extracts text from images, even when rotated or skewed. Object Detection identifies and locates specific objects (like a 'FRAGILE' sticker) within the image.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Image Classification and OCR (Read API)
Why it's wrong here
Incorrect. Image Classification can classify the entire image but does not provide location information for the sticker. The scenario requires detecting the sticker's presence, which Object Detection does better.
- ✗
Object Detection and Face Detection
Why it's wrong here
Incorrect. While Object Detection can locate the sticker, Face Detection is designed for human faces and is not useful for reading labels or detecting stickers. OCR is needed for text.
- ✗
Image Classification and Face Detection
Why it's wrong here
Incorrect. Neither capability addresses the need to read rotated text (OCR is needed) nor does Face Detection help with sticker detection.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse Image Classification (which labels the whole image) with Object Detection (which finds specific objects), leading them to pick Option B, thinking classification can detect a sticker, when it cannot provide location or multiple object instances.
Trap categories for this question
Scenario analysis trap
Incorrect. Image Classification can classify the entire image but does not provide location information for the sticker. The scenario requires detecting the sticker's presence, which Object Detection does better.
Detailed technical explanation
How to think about this question
The OCR Read API (part of Azure Computer Vision) uses a deep-learning-based recognition engine that handles rotated, skewed, and varied-font text by first detecting text regions via a text detection model (e.g., CRAFT), then recognizing characters with a sequence-to-sequence model. Object Detection in Azure uses models like YOLO or Faster R-CNN to output bounding boxes and class labels for objects (e.g., 'FRAGILE sticker'), enabling precise localization. In a real-world conveyor belt system, these APIs would be called sequentially: first Object Detection to find the sticker region, then OCR to read any text on the label, or vice versa depending on workflow.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
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FAQ
Questions learners often ask
What does this AI-900 question test?
Describe features of computer vision workloads on Azure — This question tests Describe features of computer vision workloads on Azure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: OCR (Read API) and Object Detection — The scenario requires reading rotated or skewed text from shipping labels (handled by the OCR Read API, which extracts printed and handwritten text from images, even when rotated or skewed) and detecting whether a 'FRAGILE' sticker is present (handled by Object Detection, which identifies and locates specific objects—like stickers—within an image). Option A correctly pairs these two capabilities to meet both requirements.
What should I do if I get this AI-900 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
This AI-900 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-900 exam.
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