AI-900 Describe features of computer vision workloads on Azure Practice Test 4 — 15 Questions

Question 1

A home security system uses a camera to detect common household objects such as a person, a pet, a bag, or a package. The system needs to identify the presence and location (bounding box) of these objects in images. The development team wants to use a prebuilt Azure AI service without any custom training. Which Azure Computer Vision capability should they use?

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

Accepted Answer

Image Analysis – Object Detection. (Image Analysis – Object Detection) is correct because the requirement is to identify both the presence and location (bounding box) of common household objects in images using a prebuilt Azure AI service without custom training. Azure Computer Vision's Image Analysis – Object Detection provides pre-trained models that can detect multiple objects, including people, pets, bags, and packages, and return their bounding box coordinates, exactly matching the scenario.

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Optical Character Recognition (OCR)

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Image Analysis – Image Captioning

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Custom Vision

Question 2

A retail store wants to use Azure Computer Vision to count the number of people entering a store from live video feeds. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

People Detection. People Detection is a specialized prebuilt capability within Azure Computer Vision that is designed specifically to detect and count people in images or video frames. Unlike generic object detection, it is optimized for identifying human figures regardless of pose or occlusion, making it ideal for counting store entries from live video feeds.

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Image classification

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Object detection

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Optical Character Recognition (OCR)

Question 3

A social media platform wants to automatically detect and flag images that contain violent content or adult material before they are published. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Image Analysis (with content moderation). Azure Computer Vision's Image Analysis includes a content moderation feature that can detect adult, racy, and violent content in images. This prebuilt capability is specifically designed to flag inappropriate material before publication, making it the ideal choice for the social media platform's requirement.

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Optical Character Recognition (OCR)

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Object Detection

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Background Removal

Question 4

A retail company wants to use Azure Computer Vision to monitor product availability on shelves. They need to detect the presence and location of any product (e.g., a box, a bottle) on a shelf image, but they do not need to identify the specific product brand or type. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Object detection. Object detection is the correct choice because it identifies and locates multiple objects within an image by drawing bounding boxes around each detected item. For monitoring product availability on shelves, the company needs to know both the presence and position of products (e.g., boxes, bottles) without identifying specific brands or types, which aligns exactly with object detection's capability to output class labels (e.g., 'product') and coordinates.

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Image classification

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Optical Character Recognition (OCR)

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Semantic segmentation

Question 5

A logistics company wants to automatically extract the tracking numbers, delivery addresses, and sender names from scanned shipping labels. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). (Optical Character Recognition, or OCR) is correct because the task requires extracting text (tracking numbers, addresses, sender names) from scanned images. Azure Computer Vision's OCR API is specifically designed to detect and read printed or handwritten text from images, returning the text content along with bounding boxes. Object Detection, Image Classification, and Face Detection do not extract text, making OCR the appropriate prebuilt capability.

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Object Detection

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Image Classification

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Face Detection

Question 6

A city traffic department wants to use Azure Computer Vision to automatically analyze live video feeds from traffic cameras. They need to detect and locate common objects such as cars, pedestrians, and bicycles in each frame. The department does not have a labeled dataset for custom training. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Object Detection (part of Image Analysis 4.0). The Object Detection capability within Image Analysis 4.0 can detect and locate common objects (e.g., cars, pedestrians, bicycles) in images or video frames without requiring any labeled dataset. It provides bounding box coordinates for each detected object, which directly meets the requirement to 'detect and locate' objects in live traffic camera feeds.

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Image Analysis (descriptive tags and captions)

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Optical Character Recognition (OCR) API

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Custom Vision object detection

Question 7

A manufacturing company wants to use Azure Computer Vision to inspect products on an assembly line for defects. They have a labeled dataset with images of defective and non-defective products. They need to not only classify products as defective or not, but also identify the exact location of the defect (e.g., a crack) in the image. Which Azure Computer Vision capability should they use?

Accepted Answer

Custom Vision object detection. Custom Vision object detection is the correct choice because it not only classifies images (defective vs. non-defective) but also localizes defects by drawing bounding boxes around them. The labeled dataset with defect locations directly supports training a model to output both class labels and spatial coordinates, which is exactly what object detection provides.

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Custom Vision image classification

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Azure Face API

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Optical Character Recognition (OCR)

Question 8

A company wants to use Azure Computer Vision to automatically analyze images of handwritten forms and extract the text for data entry. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Azure Computer Vision's Optical Character Recognition (OCR) capability is specifically designed to extract printed or handwritten text from images, including forms. It uses the Read API, which is optimized for text-heavy documents and supports handwritten text recognition, making it the correct choice for this scenario.

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Image Analysis

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Face API

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Object Detection

Question 9

A company needs to extract text from scanned invoices and receipts. Which Azure services are suitable for this task? (Select all that apply.)

Accepted Answer

Computer Vision. Option A, Computer Vision, is correct because its Read/OCR capability (the Read API) extracts printed and handwritten text from images and scanned documents, which directly fits pulling text from scanned invoices and receipts. Option B, Form Recognizer, is correct because it is purpose-built for document understanding: its prebuilt receipt model and invoice model return structured fields (merchant, totals, line items, dates) from receipts and invoices, going beyond raw OCR. Option C, Text Analytics, is not suitable because it operates on already-extracted text to perform sentiment analysis, key phrase extraction, named entity recognition, and language detection—it does not perform OCR on scanned images. Option D, Custom Vision, is not suitable because it is an image classification/object detection service that labels or locates objects in images, not a text-extraction or document-understanding service.

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Text Analytics

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Custom Vision

Question 10

A retail chain wants to automatically detect which specific products are missing from store shelves by analyzing images from in-store cameras. Each product has a distinct shape and label. Which Azure Computer Vision capability is most appropriate for this task?

Accepted Answer

B) Object Detection. Object Detection (Option B) is the correct choice because it can identify and locate multiple products within an image by drawing bounding boxes around each detected object. This allows the system to determine which specific products are missing by comparing detected items against an expected inventory list. Image Classification would only label the entire image, not individual products, while OCR focuses on text extraction and Facial Recognition identifies people.

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A) Image Classification

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C) Optical Character Recognition (OCR)

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D) Facial Recognition

Question 11

A manufacturing company wants to use computer vision to inspect products on an assembly line. They need to identify and locate specific types of defects (e.g., scratch, dent, crack) in product images. Which Azure Computer Vision capability should they use?

Accepted Answer

Object Detection. Object Detection is the correct choice because it not only classifies defects (e.g., scratch, dent, crack) but also provides bounding box coordinates to locate each defect within the product image. This meets the requirement to both identify and locate specific defect types on the assembly line.

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Image Classification

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Optical Character Recognition (OCR)

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Face Detection

Question 12

A museum wants to create an app that allows visitors to take a photo of a painting and receive information about the artist, year, and style. The app needs to identify the painting from a database of thousands of artworks. Which Azure Computer Vision capability is most suitable?

Accepted Answer

Image classification. Image classification is the correct choice because the app needs to assign a single label (the specific painting) to the entire photo. Azure Computer Vision's image classification models are trained to recognize and categorize entire images into predefined classes, which matches the requirement of identifying a painting from a database of thousands of artworks based on the visual content of the photo.

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Optical Character Recognition (OCR)

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Object detection

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Face detection

Question 13

A government agency needs to digitize thousands of handwritten application forms so that the text can be searched and processed. Which Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (Read API). Optical Character Recognition (Read API), because the agency needs to extract printed or handwritten text from images of application forms and make it searchable and processable. The Read API is specifically designed for this purpose, handling both printed and handwritten text, and is part of Azure Computer Vision's OCR capabilities.

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Object detection

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Image classification

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Face detection

Question 14

A retail company wants to build a solution that automatically reads the printed text on product labels to update inventory records. The labels contain alphanumeric characters and are in various fonts and sizes. Which Azure Cognitive Service should they use?

Accepted Answer

Azure Computer Vision - OCR. Azure Computer Vision's OCR (Optical Character Recognition) API is specifically designed to extract printed text from images, handling various fonts, sizes, and alphanumeric characters. This makes it the ideal choice for reading product labels to update inventory records, as it can process the diverse label formats commonly found in retail environments.

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Azure Face Service

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Azure Form Recognizer

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Azure Video Indexer

Question 15

A security company needs to monitor a warehouse using video cameras. They want to detect whether any persons are present in a given frame and also know their approximate locations. Which Azure Computer Vision capability should they use?

Accepted Answer

Object detection. Object detection is the correct choice because it not only identifies whether persons are present in a video frame but also provides bounding box coordinates indicating their approximate locations. This capability is specifically designed to locate multiple objects of interest within an image, which directly matches the requirement of detecting persons and knowing where they are.

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Image classification

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Semantic segmentation

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Optical Character Recognition (OCR)