AI-103 Computer Vision Practice Test 3 — 15 Questions

Question 1

When creating a new project in the Custom Vision portal, you need to choose a classification type. You want to tag an image with multiple independent tags (e.g., 'outdoor', 'sunset', 'mountain'). Which classification type should you select?

Choose an answer to begin — your selection is scored in the full session.

Accepted Answer

Multilabel. Multilabel classification lets a single image carry multiple independent tags simultaneously, which is exactly what is needed when an image can be 'outdoor', 'sunset', and 'mountain' at the same time. Each tag is evaluated independently, so the model outputs a probability per tag rather than forcing a single winning class. This matches the requirement of applying multiple non-exclusive labels.

Answer

Object Detection

Answer

Binary Classification

Answer

Multiclass

Question 2

Your application processes receipt images using Azure AI Vision Read API. You need to extract text specifically from tables within the receipts. Which service is better suited for advanced table structure and key-value pair extraction compared to base Azure AI Vision Read?

Accepted Answer

Azure AI Document Intelligence. Azure AI Document Intelligence (formerly Form Recognizer) is purpose-built for structured document extraction, including tables, key-value pairs, and layout analysis. Its prebuilt receipt model and general document/layout models return structured JSON with table cells, row/column spans, and semantic key-value associations that the base Read API does not provide. The Read API only returns raw text lines and words with bounding boxes, without table structure or field semantics.

Answer

Azure AI Face Service

Answer

Custom Vision Service

Answer

Azure AI Content Safety

Question 3

You are configuring a secure enterprise architecture where Azure AI Vision calls must not traverse the public internet. You create a private endpoint for your Azure AI Services resource in your Virtual Network. Which DNS configuration step is required for client applications within the VNet to resolve the private endpoint correctly?

Accepted Answer

Configure Azure Private DNS zones corresponding to the cognitive services DNS zone and link it to your VNet.. When you create a private endpoint for an Azure AI Services resource, the private IP is associated with the service's public DNS name (for example, <resource>.cognitiveservices.azure.com). For clients in the VNet to resolve that name to the private IP instead of the public IP, you must create an Azure Private DNS zone named privatelink.cognitiveservices.azure.com and link it to the VNet, with an A record mapping the resource to the private endpoint IP.

Answer

Add the endpoint IP to the local hosts file of every Azure AI Vision instance.

Answer

Configure public DNS records on your corporate DNS server to point to the public IP.

Answer

Modify the routing table to drop all DNS traffic.

Question 4

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?

Accepted Answer

Add training images containing partially occluded objects and ensure they are correctly tagged.. Occlusion handling is a data problem: if the training set lacks examples of partially occluded objects, the model never learns to recognize them. Adding training images that contain partially occluded instances of the target class and tagging them with accurate bounding boxes teaches the model to detect objects even when parts are hidden, improving real-world performance.

Answer

Switch from General domain to Food domain.

Answer

Lower the confidence threshold to 0.01.

Answer

Increase image compression artifacts.

Question 5

You are developing a mobile application that captures business card photos and extracts contact information. Which Azure AI Vision feature is specifically designed to extract printed and handwritten text lines and words?

Accepted Answer

Read. The Read feature in Azure AI Vision is specifically designed for OCR, extracting printed and handwritten text lines and words from images. It is optimized for text-heavy images like business cards, documents, and receipts. This makes it the correct choice for capturing contact information from business card photos.

Answer

Image Tagging

Answer

Dense Captions

Answer

Brand Detection

Question 6

You want to detect whether corporate logos appear in user-submitted images using Azure AI Vision. Which visual feature parameter should you request?

Accepted Answer

features=brands. Azure AI Vision's Analyze Image API supports a 'brands' visual feature that detects corporate logos and brands within an image, returning brand names and confidence scores. Requesting features=brands enables this specific detection capability, which is distinct from general object or tag detection.

Answer

features=domain-specific

Answer

features=objects

Answer

features=tags

Question 7

You are configuring a Custom Vision project to classify images of plant diseases. You notice that some image files uploaded via the API are rejected because they exceed the maximum allowed file size. What is the maximum image file size supported by Custom Vision for training?

Accepted Answer

6 MB. Custom Vision enforces a maximum training image file size of 6 MB per image. Images larger than this are rejected by the API during upload, regardless of their dimensions or format. This limit applies to training images, not prediction images, which have their own constraints.

Answer

2 GB

Answer

500 KB

Answer

50 MB

Question 8

You are using Azure AI Vision Read API in your application. You want to ensure that the extracted text blocks return word-level bounding polygons rather than just line-level bounding boxes. What parameter or response structure should you examine?

Accepted Answer

Examine the 'words' array within each returned 'lines' object in the JSON response payload.. The Azure AI Vision Read API returns OCR results as a hierarchy of pages → lines → words, and each word object contains a bounding polygon (boundingPolygon) with four (x,y) points. To get word-level polygons, you examine the 'words' array nested inside each 'lines' object in the JSON response — no query parameter is needed.

Answer

Add ?wordLevel=true to the query string.

Answer

Call the legacy OCR endpoint instead.

Answer

Set the model-version parameter to v2.0.

Question 9

You are optimizing performance for a real-time video analytics pipeline that sends video frames to Azure AI Vision. Due to network bandwidth constraints, you need to reduce payload sizes while maintaining high OCR accuracy. What is the recommended approach?

Accepted Answer

Encode frames as optimized JPEG images with appropriate resolution scaling, ensuring text remains legible.. Optimized JPEG encoding with resolution scaling reduces payload size while preserving text legibility, which is the key requirement for OCR accuracy. JPEG's lossy compression is well-suited for photographic frames, and scaling to the minimum resolution that keeps text readable balances bandwidth and accuracy. This is the recommended approach for bandwidth-constrained real-time OCR pipelines.

Answer

Convert frames to uncompressed 32-bit BMP format.

Answer

Extract audio tracks instead of video frames.

Answer

Send raw YUV byte arrays directly without image containerization.

Question 10

You need to programmatically delete an iteration of a Custom Vision model that performed poorly. Which API method should you invoke?

Accepted Answer

DELETE /customvision/v3.3/Training/{projectId}/iterations/{iterationId}. The Custom Vision Training API exposes iteration deletion via the HTTP DELETE method on the path /customvision/v3.3/Training/{projectId}/iterations/{iterationId}. Invoking DELETE on that resource removes the specified iteration from the project. This is the standard RESTful pattern for deleting a subordinate resource identified by its parent project and iteration IDs.

Answer

PUT /customvision/v3.3/Training/{projectId}/iterations/{iterationId}

Answer

GET /customvision/v3.3/Training/{projectId}/iterations/{iterationId}/purge

Answer

POST /customvision/v3.3/Training/{projectId}/iterations/{iterationId}/delete

Question 11

You are training a Custom Vision multiclass classification model for retail products. After training, you notice that the precision is high, but the recall is low for a specific product category. What does low recall indicate?

Accepted Answer

The model is missing many actual instances of that product category (high false negatives).. Recall measures the proportion of actual positive instances that the model correctly identifies. Low recall means the model is missing many actual instances of the product category, resulting in a high number of false negatives. High precision with low recall indicates the model is conservative: when it predicts the category it is usually right, but it fails to catch many true cases.

Answer

The training dataset had zero images for that category.

Answer

The model is incorrectly predicting that product when it is not present (high false positives).

Answer

The probability threshold is set too high for all classes uniformly.

Question 12

Your application integrates Azure AI Vision and processes images stored in an Azure Blob Storage container. To adhere to security best practices, you want to avoid exposing public blob URLs. How should you provide the image to the Image Analysis API?

Accepted Answer

Download the image bytes in your application code and send them in the binary request body (application/octet-stream).. The Image Analysis API accepts image bytes directly in the request body with Content-Type: application/octet-stream, so your application can read the blob using its own credentials (managed identity, SAS, or connection string) and forward the bytes without ever making the blob publicly accessible. This keeps the storage account private and avoids exposing URLs. The API also supports image URLs, but only if the URL is publicly reachable — which violates the stated security requirement.

Answer

Use FTP to transfer images to the vision service endpoint.

Answer

Permanently change the blob container access level to Public Read.

Answer

Mount the Blob Storage container directly to the Azure AI Vision service via NFS.

Question 13

You are training a Custom Vision object detection model. You have 1,000 images, but only 200 of them contain the rare object you want to detect. The other 800 images are background images without the object. What impact will this class imbalance have on training, and how should you address it?

Accepted Answer

Ensure that you have tagged at least 15 bounding boxes per tag; having background images is beneficial for reducing false positives.. Custom Vision object detection requires a minimum of 15 tagged bounding boxes per tag for a tag to be trainable, and background (negative) images are explicitly beneficial because they teach the model what the object is not, reducing false positives. With only 200 positive images, keeping the 800 backgrounds provides valuable negative examples. The correct guidance is to ensure sufficient tagged instances while retaining background images.

Answer

Reduce training iteration time to 1 minute.

Answer

Convert the project to multilabel classification.

Answer

Delete all 800 background images immediately, as they will cause training to fail.

Question 14

You are building an image search engine. You want to extract visual feature tags from user photos using Azure AI Vision 4.0. Which visual feature should you request?

Accepted Answer

features=tags. The features=tags parameter in Azure AI Vision 4.0 returns a list of content tags describing the objects, scenes, and concepts detected in an image, which is exactly what an image search engine needs for indexing and retrieval. Tags are the visual feature purpose-built for extracting searchable descriptors from photos.

Answer

features=read

Answer

features=caption

Answer

features=smartCrops

Question 15

Which HTTP status code does the Azure AI Vision Read API return upon successfully initiating an asynchronous OCR analysis job?

Accepted Answer

202 Accepted. The Read API is asynchronous: when you POST an image or URL to the Read endpoint, it returns 202 Accepted with an Operation-Location header. You then poll that URL until the job completes and returns 200 OK with results.

Answer

204 No Content

Answer

200 OK

Answer

201 Created