AI-102 Implement computer vision solutions Practice Question
A company wants to moderate user-generated images for adult content. Which Azure AI Vision feature should they use?
⚠ Common exam trap
Candidates often assume Custom Vision is needed for any custom moderation task, but Azure AI Vision's Analyze Image API already includes built-in adult content detection, making custom training unnecessary for this specific use case.
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
✓
Analyze Image API with moderation categories
The Analyze Image API in Azure AI Vision includes built-in moderation categories for detecting adult, racy, and gory content in images. This feature is specifically designed for content moderation without requiring custom training, making it the correct choice for moderating user-generated images for adult content.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Custom Vision with a custom adult classifier
Why it's wrong here
Custom Vision trains a bespoke classifier, requiring labelled adult images and training time, whereas the scenario needs built-in moderation. It is tempting because custom classifiers suit organisation-specific categories, but Azure AI Content Safety's image analysis returns adult and racy flags out of the box without training data.
- ✗
Face API
Why it's wrong here
Face API detects, verifies and identifies human faces; it returns no adult or racy classification, so it cannot moderate imagery. It is tempting because it analyses images and is often grouped with vision services, but it would be correct for facial recognition, attendance or identity verification scenarios, not content moderation.
- ✓
Analyze Image API with moderation categories
Why this is correct
The Analyze Image API returns adult and racy classification flags directly from its moderation categories, satisfying the requirement to detect adult content in user-generated images. Unlike standalone classifiers, it performs this assessment within a single vision call, so no separate moderation service or custom model is needed.
- ✗
OCR
Why it's wrong here
OCR extracts printed or handwritten text from images, so it cannot detect adult visual content at all. It is tempting because OCR is an Azure AI Vision capability that processes images, but its purpose is reading text for document digitisation or accessibility, not classifying imagery by content category.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 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-102 exam.