AI-103 Computer Vision Practice Question
You are troubleshooting a Custom Vision object detection model that has low precision and high false-positive rates for a specific object class. During data analysis, you notice that negative images (images without the object) lack background variety. What is the recommended remediation step?
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 diverse negative images containing background environments similar to where false positives occur.
Adding more diverse negative images that resemble difficult backgrounds helps the model distinguish the target object from confusing background elements.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the probability threshold in the prediction API call.
Why it's wrong here
While threshold adjustment filters results, fixing the root cause with better negative training data is the correct machine learning remediation.
- ✗
Remove all tagged bounding boxes and retrain as a multi-class classification model.
Why it's wrong here
Converting object detection to classification will lose spatial location data.
- ✗
Apply aggressive data augmentation to duplicate existing positive images.
Why it's wrong here
Duplicating positive images does not fix false positives caused by lack of negative training context.
- ✓
Add diverse negative images containing background environments similar to where false positives occur.
Why this is correct
Adding challenging negative images helps reduce false positives by providing negative context.
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.