AI-103 Computer Vision Practice Question
You are testing a Custom Vision object detection model using the test image feature in the portal. You notice that objects are detected with low confidence scores. You want to improve the model's performance without adding more training images. What can you adjust in the training settings?
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
✓
Increase the training time budget in advanced training settings.
While training data is primary, training iterations allow selecting different training time budgets or domains, but adjusting the probability threshold in prediction evaluation helps filter results. However, re-training with advanced training time settings can improve model accuracy.
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 object detection to multiclass classification.
Why it's wrong here
Changing problem types changes the output format entirely and does not fix low confidence for bounding boxes.
- ✓
Increase the training time budget in advanced training settings.
Why this is correct
Increasing the training time allows the underlying neural network more epochs to converge on complex patterns.
- ✗
Decrease the image resolution setting in project properties.
Why it's wrong here
Lowering resolution degrades detail and harms object detection performance.
- ✗
Disable data augmentation.
Why it's wrong here
Data augmentation generally helps generalization rather than hurting it.
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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
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