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 needs to automatically extract printed and handwritten text from scanned shipping labels. Which Azure Computer Vision capability should they use?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Computer Vision Read API
The Azure Computer Vision Read API is specifically designed to extract printed and handwritten text from images and documents, such as scanned shipping labels. It uses optical character recognition (OCR) to process text in various languages and formats, making it the correct choice for this logistics scenario.
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.
✗
Azure Face API
Why it's wrong here
Face API detects and recognizes human faces, not text extraction from documents.
✓
Azure Computer Vision Read API
Why this is correct
Read API performs OCR to extract printed and handwritten text from images, suitable for shipping labels.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Custom Vision
Why it's wrong here
Custom Vision allows training custom image classification or object detection models, not text extraction.
✗
Azure Video Indexer
Why it's wrong here
Video Indexer extracts insights from video files, not from static images like labels.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Custom Vision with OCR capabilities, assuming it can be trained for text extraction, but Custom Vision is limited to object detection and classification, not text recognition.
Detailed technical explanation
How to think about this question
The Read API employs a deep-learning-based OCR engine that supports both printed and handwritten text, processing images asynchronously to handle large volumes. It returns results with bounding boxes, confidence scores, and text lines, which can be integrated into automated workflows for logistics document processing. A subtle behavior is that the API performs best with high-contrast images and may struggle with heavily skewed or low-resolution labels, requiring preprocessing for optimal accuracy.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AI-900 question in full detail.
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: Azure Computer Vision Read API — The Azure Computer Vision Read API is specifically designed to extract printed and handwritten text from images and documents, such as scanned shipping labels. It uses optical character recognition (OCR) to process text in various languages and formats, making it the correct choice for this logistics scenario.
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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Question Discussion
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