AI-102 Implement computer vision solutions Practice Question
You are building a computer vision solution to detect defects on a manufacturing assembly line. The solution must process images in real-time with low latency, and you need to choose an Azure service. Which service should you use?
⚠ Common exam trap
It's easy for candidates to choose Azure Computer Vision API (Option A) because it sounds like a general-purpose vision service, but they overlook the requirement for custom defect detection, which necessitates a trainable model like Custom Vision.
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
✓
Azure Custom Vision
Azure Custom Vision is the correct choice because it allows you to train a custom image classification or object detection model tailored to detect specific manufacturing defects. It supports real-time, low-latency inference via a Docker container deployed to edge devices or directly through the prediction API, meeting the assembly line's performance requirements.
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 Computer Vision API
Why it's wrong here
The Computer Vision API is a pre-built, cloud-hosted service reached over the network, so round-trip latency makes it unsuitable for real-time line inspection. It suits general image tagging and OCR. Custom Vision or an edge-deployed model is needed when inference must run locally at low latency.
- ✗
Azure Video Indexer
Why it's wrong here
Video Indexer analyses stored or streamed video for insights like transcription, faces and topics, operating on media rather than per-frame defect detection. It tempts because it processes visual media at scale, but its batch-oriented pipeline cannot meet low-latency inline inspection requirements.
- ✗
Azure Form Recognizer
Why it's wrong here
Azure Form Recognizer extracts text and structured fields from documents such as invoices and forms; it performs no defect detection on product images, so it cannot satisfy the assembly-line requirement. It would be the right choice when parsing scanned paperwork into JSON, for example automating invoice or receipt data capture.
- ✓
Azure Custom Vision
Why this is correct
Azure Custom Vision trains and hosts a purpose-built image classification or object detection model, letting you deploy a compact domain-specific model to a prediction endpoint for low-latency inline defect scoring, satisfying the real-time assembly-line constraint.
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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.