AI-102 Implement computer vision solutions Practice Question
You are designing a solution to detect brand logos in social media images. The logos vary in size and orientation. You need to achieve high accuracy with minimal false positives. Which approach should you recommend?
⚠ Common exam trap
A common mix-up: candidates confuse Azure Computer Vision's pre-built domain-specific models (which cover only landmarks, celebrities, and general objects) with the ability to detect custom logos, leading them to choose option C instead of recognizing that Custom Vision is required for custom object detection.
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
✓
Train an Azure Custom Vision object detection model with labeled logo images.
Azure Custom Vision allows you to train a custom object detection model with your own labeled dataset of brand logos, enabling high accuracy for specific logo shapes, sizes, and orientations. This approach directly addresses the need for minimal false positives by learning the exact visual features of the logos, unlike generic pre-built models.
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 Azure Computer Vision Describe API to generate captions and filter by logo mentions.
Why it's wrong here
Not reliable for accurate detection.
- ✓
Train an Azure Custom Vision object detection model with labeled logo images.
Why this is correct
Custom object detection can learn to detect logos in various conditions.
- ✗
Use Azure Computer Vision Analyze API with domain-specific models.
Why it's wrong here
Analyze API doesn't support custom object detection.
- ✗
Use Azure Form Recognizer to extract logo positions from images.
Why it's wrong here
Form Recognizer is for structured documents.
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