AI-102 Practice Test 26 — 15 Questions

Question 1

Your team is building a mobile app that uses Azure AI Computer Vision to extract text from business cards. The app must handle cards in multiple languages (English, French, German). Which feature of the Computer Vision API should you use?

Accepted Answer

Read API. Option D is correct because the Read API supports multiple languages and is designed for OCR. The OCR API (A) is older and less accurate. Describe Image (B) generates captions, not text extraction. Recognize Text (C) is deprecated.

Answer

OCR API

Answer

Recognize Text

Answer

Describe Image

Question 2

You are developing a solution to detect defects on a manufacturing assembly line using computer vision. The solution must classify images as 'defective' or 'non-defective'. You have a limited set of labeled images (500 per class). Which approach should you recommend?

Accepted Answer

Use Azure AI Custom Vision with image classification. The correct answer is to use a custom model with transfer learning via Azure AI Custom Vision. This is designed for small datasets and allows classification with limited labeled data. Option A is wrong because pre-built models are not trained for specific defects. Option B is wrong because object detection is overkill and not focused on classification. Option D is wrong because training a model from scratch requires much more data.

Answer

Use Azure AI Vision Image Analysis with a pre-built model

Answer

Use Azure AI Custom Vision with object detection

Answer

Train a deep learning model from scratch using Azure Machine Learning

Question 3

An application uses Azure AI Vision to analyze images and extract text. The application crashes when processing images with embedded barcodes. You suspect the issue is related to the image pre-processing. Which step should you add to the pipeline to resolve the issue?

Accepted Answer

Detect and remove barcodes from the image before OCR. The correct answer is to add a barcode detection and removal step before OCR. Barcodes can confuse OCR services because they contain patterns that may be interpreted as text, causing errors. Option A is wrong because adjusting contrast does not address barcode interference. Option B is wrong because adding more training data is for custom models, not pre-built OCR. Option D is wrong because compressing the image may reduce quality and exacerbate the issue.

Answer

Increase the image contrast before sending to the OCR engine

Answer

Add more training data with barcodes to the OCR model

Answer

Resize the image to a smaller resolution to reduce barcode impact

Question 4

Which TWO Azure AI services provide capabilities to detect and analyze faces in images? (Choose two.)

Accepted Answer

Azure AI Face API. Azure AI Face API is specifically for face detection and analysis. Azure AI Vision Image Analysis can also detect faces as part of its object detection. Option C is wrong because Video Indexer analyzes video, not images. Option D is wrong because Custom Vision is not pre-built for faces. Option E is wrong because Document Intelligence is for document analysis.

Answer

Azure AI Custom Vision

Answer

Azure AI Document Intelligence

Answer

Azure Video Indexer

Question 5

You are calling the Azure AI Vision Image Analysis API with the above JSON request. The API returns a response that includes tags, objects, and a caption. However, the caption does not describe the image accurately. Which change should you make to improve the caption quality?

Accepted Answer

Set gender-neutral-caption to false. The correct answer is to remove 'gender-neutral-caption' or set it to false. Gender-neutral captions may be less descriptive. Option A is wrong because the model-version is already latest. Option B is wrong because language is already English. Option D is wrong because adding 'read' feature is for OCR, not caption quality.

Answer

Change model-version to a newer version

Answer

Add 'read' feature to the request

Answer

Set language to 'en-US'

Question 6

You are deploying a Custom Vision object detection model to an Azure Container Instance for real-time inference. The model must respond within 500 ms. The default container runs on CPU. What should you do to meet the latency requirement?

Accepted Answer

Export the model as a Dockerfile with GPU support and deploy to a GPU-enabled ACI.. Option D is correct because using a GPU-optimized container and a GPU-enabled Azure Container Instance will significantly reduce inference time. Increasing the number of CPU cores (A) helps but may not meet 500 ms for object detection. Using Azure Functions (B) adds cold start latency. Using Cognitive Services container (C) is not correct for Custom Vision export.

Answer

Increase the number of CPU cores in the container instance.

Answer

Deploy the model to Azure Functions with a Premium plan.

Answer

Use the Cognitive Services Computer Vision container instead.

Question 7

You need to detect if a photo contains adult or racy content. Which Azure AI Computer Vision feature should you use?

Accepted Answer

Analyze Image API with the 'adult' parameter. Option A is correct because the Analyze Image API with the adult parameter is designed to detect adult, racy, and gory content. Describe Image (B) generates captions. OCR (C) extracts text. Tag Image (D) returns tags.

Answer

Describe Image API

Answer

OCR API

Answer

Tag Image API

Question 8

Your company wants to moderate user-uploaded images for adult content. Which Azure AI service should you use?

Accepted Answer

Azure AI Content Safety. Azure AI Content Safety is specifically designed to detect adult and offensive content. It can analyze images for adult content.

Answer

Azure AI Face

Answer

Azure AI Document Intelligence

Answer

Azure AI Vision Image Analysis

Question 9

You need to build a solution that reads text from images in multiple languages, including Arabic and English, and translates the text into English. The solution must preserve the original layout as much as possible. Which combination of Azure AI services should you use?

Accepted Answer

Azure AI Document Intelligence Read and Azure AI Translator. The correct answer is to use Azure AI Document Intelligence Read for OCR and then Azure AI Translator for translation. Read supports multiple languages and preserves layout, and Translator can translate the extracted text. Option A is wrong because Azure AI Vision OCR does not preserve layout as well. Option C is wrong because Azure AI Language is for NLP tasks, not translation. Option D is wrong because Azure AI Speech is for speech-to-text, not OCR.

Answer

Azure AI Document Intelligence Read and Azure AI Language

Answer

Azure AI Vision OCR and Azure AI Translator

Answer

Azure AI Speech and Azure AI Translator

Question 10

A manufacturing company uses Azure AI Custom Vision to detect defects on a production line. The model was trained with 500 images per class and achieves 95% accuracy. After deployment, the model's accuracy drops to 80% due to changes in lighting conditions. What is the most effective first step to improve the model's robustness?

Accepted Answer

Capture additional images under the new lighting and retrain the model.. Option C is correct because retraining with images that represent the new lighting conditions will directly address the distribution shift. Adding more images of the original lighting (A) won't help with new conditions. Adjusting probability threshold (B) might change precision/recall but not robustness. Using AutoML (D) is not directly applicable to Custom Vision.

Answer

Reduce the probability threshold to increase recall.

Answer

Use Azure AutoML to automatically find the best algorithm.

Answer

Add more images from the original lighting conditions to the training set.

Question 11

You are developing a mobile app that allows users to take a photo of a product and get information about it. The app must identify the product from the image. Which Azure AI service should you use?

Accepted Answer

Azure AI Custom Vision with image classification. The correct answer is Azure AI Custom Vision with image classification. Custom Vision can be trained to recognize products from images. Option A is wrong because object detection is for locating objects, not classifying the entire image. Option C is wrong because Face API is for faces. Option D is wrong because OCR is for text extraction.

Answer

Azure AI Vision OCR

Answer

Azure AI Face API

Answer

Azure AI Custom Vision with object detection

Question 12

You are deploying a custom image classification model using Azure AI Custom Vision. The model must achieve high accuracy on a dataset with subtle differences between classes. However, the training set is small (200 images per class). Which strategy should you use to improve model performance?

Accepted Answer

Use transfer learning with a pre-trained model and fine-tune. Transfer learning with a pre-trained model is the standard approach for small datasets. Fine-tuning allows the model to leverage learned features.

Answer

Enable hyperparameter tuning and increase the number of iterations

Answer

Apply aggressive data augmentation and train from scratch

Answer

Use a larger batch size and train for more epochs

Question 13

You are tasked with creating a solution that can identify and count people in a retail store to analyze foot traffic. Which TWO Azure AI services can be used together?

Accepted Answer

Azure AI Video Indexer. Azure AI Vision's people detection counts people in images. Video Indexer can analyze video streams for people counting over time.

Answer

Azure AI Content Safety

Answer

Azure AI Document Intelligence

Answer

Azure AI Face

Question 14

Which TWO Azure AI services can be used to detect objects in images?

Accepted Answer

Custom Vision. Option A and B are correct because Custom Vision and Computer Vision Object Detection both support object detection. Option C is wrong because Face API detects faces, not generic objects. Option D is wrong because Document Intelligence extracts text and structure. Option E is wrong because Video Indexer analyzes video, not images.

Answer

Video Indexer

Answer

Face API

Answer

Azure AI Document Intelligence

Question 15

You are developing an application that processes images of handwritten forms. The forms contain checkboxes that may be checked or unchecked. Which Azure AI service should you use to detect the state of the checkboxes?

Accepted Answer

Azure AI Document Intelligence. Option B is correct because Azure AI Document Intelligence (formerly Form Recognizer) is designed to extract information from forms, including checkboxes. The other options are not specialized for checkbox detection: Computer Vision for OCR, Custom Vision for image classification, and Language Service for text analysis.

Answer

Azure AI Custom Vision

Answer

Azure AI Language

Answer

Azure AI Computer Vision