AI-103 Computer Vision Practice Question
You are analyzing performance metrics of a Custom Vision object detection iteration. You observe a Mean Average Precision (mAP) of 88%, but when testing with real-world user photos, the model fails to detect objects that are partially occluded. What should you do to improve occlusion handling?
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
✓
Add training images containing partially occluded objects and ensure they are correctly tagged.
To improve detection of occluded objects, you must include training images that feature partially blocked or occluded instances of the target objects.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch from General domain to Food domain.
Why it's wrong here
Switching domains is irrelevant unless the objects are specifically food items.
- ✗
Lower the confidence threshold to 0.01.
Why it's wrong here
Lowering the threshold introduces excessive false positives without teaching the model about occlusion.
- ✓
Add training images containing partially occluded objects and ensure they are correctly tagged.
Why this is correct
Training with occluded examples teaches the model to recognize partial features of the object.
- ✗
Increase image compression artifacts.
Why it's wrong here
Compression artifacts degrade image quality and make recognition harder.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed August 2026 · checked against the official Microsoft exam blueprint
This AI-103 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-103 exam.