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AI-102 Practice Question: A retail company uses Azure Computer Vision to…
A retail company uses Azure Computer Vision to analyze in-store camera feeds. They recently added a new product line and updated the object detection model. However, the model fails to detect the new products. What should the company do first?
⚠ Common exam trap
Many exam-takers assume a pre-built model or a simple threshold tweak can handle new object classes, when in fact custom object detection requires retraining with labeled examples of the new items.
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
✓
Retrain the custom object detection model with images of the new products.
The model fails to detect new products because it was never trained on them. Retraining the custom object detection model with labeled images of the new products is the correct first step, as it updates the model's knowledge to recognize the new product line. Pre-built models or threshold adjustments cannot add new object classes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use the pre-built 'products' model from Computer Vision.
Why it's wrong here
Pre-built models may not include the new product line.
- ✗
Increase the confidence threshold in the API call.
Why it's wrong here
Adjusting threshold does not add new objects to detect.
- ✓
Retrain the custom object detection model with images of the new products.
Why this is correct
Custom models need retraining with new labeled data.
- ✗
Recreate the Computer Vision resource in a different region.
Why it's wrong here
Region change does not affect model capabilities.
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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.