AI-102 Implement computer vision solutions Practice Question
A company uses Azure AI Vision Image Analysis to generate captions for product photos. The solution must return a caption in English and a confidence score for each image. You call the Image Analysis API with the caption feature. The response does not include a confidence score. What should you do to obtain confidence scores for the captions?
⚠ Common exam trap
The trap here is assuming that the newest Image Analysis caption feature includes a confidence score, when only the legacy v3.2 description feature returns one.
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
✓
Use the older Computer Vision v3.2 Analyze Image API with the 'description' visual feature.
The legacy Computer Vision v3.2 Analyze Image API with the description feature returns a caption and a confidence score, which the newer Image Analysis 4.0 caption feature does not. To obtain confidence scores for captions, you must use the older API version. Other options either use features that lack confidence scores or rely on invalid parameters or workarounds that cannot produce a true confidence value.
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 older Computer Vision v3.2 Analyze Image API with the 'description' visual feature.
Why this is correct
The legacy Computer Vision v3.2 Analyze Image API with the description visual feature returns a caption along with a confidence score between 0 and 1. The newer Image Analysis 4.0 caption feature does not include a confidence score. To meet the requirement, you must call the v3.2 endpoint, which still provides the confidence value for the generated description.
- ✗
Call the Image Analysis API twice and compare the captions to derive a confidence score.
Why it's wrong here
Calling the API twice and comparing outputs does not produce a valid confidence score; it only checks consistency. The service does not expose a confidence metric through repeated calls, and this approach would be unreliable and costly. Confidence scores are generated by the model, not derived from comparing separate responses. This method cannot fulfill the requirement.
- ✗
Use the denseCaptions feature instead of captions.
Why it's wrong here
Dense captions provide multiple captions for different regions of an image, but they also do not return a confidence score for each caption. Switching to dense captions would change the output to multiple regional captions and still not satisfy the requirement for a confidence score. The scenario needs a single caption with a confidence value, which dense captions do not provide.
- ✗
Set the language parameter to 'en' and include the 'confidence' query parameter.
Why it's wrong here
The language parameter selects the output language, but there is no 'confidence' query parameter in the Image Analysis API. Adding a non-existent parameter will not change the response and may cause an error. Confidence scores are not controlled via query parameters; they are either returned by the service or not, depending on the feature and API version.
Go deeper
Related to this question
About these practice questions
One of 761 original AI-102 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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.