AI-900 Describe features of computer vision workloads on Azure Practice Test 6 — 15 Questions

Question 1

A retail store uses ceiling-mounted cameras to analyze customer traffic flow. They need to detect when a person enters a specific aisle and determine the direction they are walking. Which Azure Computer Vision capability should they use?

Accepted Answer

People counting (Spatial Analysis). Option C is correct because Spatial Analysis, part of Azure Computer Vision, uses ceiling-mounted cameras to track people's movement and direction in a physical space. It specifically provides people counting and trajectory analysis, making it ideal for detecting when a person enters an aisle and determining their walking direction.

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Image Analysis dense captioning

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Facial recognition

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Optical Character Recognition (OCR)

Question 2

A security company wants to use Azure Computer Vision to monitor a restricted area. They need to count the number of people present in each camera frame and draw bounding boxes around each person. Which Azure Computer Vision capability should they use?

Accepted Answer

Image Analysis (object detection). Option B (Image Analysis with object detection) is correct because Azure Computer Vision's object detection capability can identify and locate multiple instances of a specific object class—in this case, people—within an image. It returns bounding box coordinates for each detected person, enabling the security company to count individuals and draw boxes around them in each camera frame.

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Optical Character Recognition (OCR)

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Face detection

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Image classification

Question 3

A museum wants to automatically transcribe handwritten labels on historical artifacts. The handwriting varies in style and may include numbers and special characters. Which Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Optical Character Recognition (OCR) is the correct choice because it is specifically designed to extract printed or handwritten text from images, including numbers and special characters. Azure Computer Vision's OCR API can handle varied handwriting styles and convert them into machine-readable text, making it ideal for transcribing historical artifact labels.

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Image captioning

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Facial recognition

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Object detection

Question 4

A library wants to automatically generate descriptive alt text for hundreds of historical photographs in their digital archive. For each photo, the system should produce a natural-language description that includes objects present (e.g., 'a horse', 'a carriage'), the action being performed (e.g., 'pulling'), and the scene type (e.g., 'city street'). Which Azure Computer Vision capability should they use?

Accepted Answer

Image Analysis (Describe image). The Image Analysis 'Describe image' capability is designed to generate human-readable captions that summarize the content of an image, including objects, actions, and scene context. This directly matches the library's requirement to produce natural-language descriptions for historical photographs, as it uses a combination of object detection and scene understanding to output a full sentence.

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Optical Character Recognition (OCR)

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Object detection

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Face detection

Question 5

A retail store wants to analyze customer behavior in front of a specific product display. They need to determine how long each customer stands in front of the display and whether they pick up an item. Which Azure Computer Vision capability should they use?

Accepted Answer

Spatial Analysis. Spatial Analysis is the correct Azure Computer Vision capability because it is specifically designed to analyze people's movement, presence, and interactions within a physical space using video feeds. It can track how long a customer stands in front of a display (dwell time) and detect actions like picking up an item, by processing bounding boxes and skeleton data from cameras.

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Image Classification

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Optical Character Recognition (OCR)

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Object Detection

Question 6

A security company needs to identify individuals in a crowd by matching their faces against a database of known persons of interest. The system must detect faces, verify the identities, and provide a confidence score. Which Azure Computer Vision capability should they use?

Accepted Answer

Facial recognition. Azure Computer Vision's facial recognition capability is specifically designed to detect human faces in images, match them against a known database of persons, and return a confidence score for each match. This directly aligns with the security company's requirement to identify individuals in a crowd by verifying their identities against a watchlist.

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Optical character recognition (OCR)

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Image classification

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Object detection

Question 7

A retail company wants to use security cameras to automatically detect when products are removed from shelves. They need to identify the specific product type (e.g., a cereal box, a soda can) and count how many units are taken. Which Azure Computer Vision capability should they use?

Accepted Answer

Object detection. Object detection is the correct capability because it can both locate objects within an image (via bounding boxes) and classify them into specific categories (e.g., cereal box, soda can). This allows the system to identify the product type and count the number of units removed from shelves, which aligns directly with the requirement.

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Optical Character Recognition (OCR)

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Image tagging

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Face detection

Question 8

An autonomous driving company is developing a system that needs to understand the road scene at a granular level. For each pixel in a camera image, the system must classify whether it belongs to the road, a pedestrian, a vehicle, a traffic sign, or the sky. Which Azure Computer Vision capability should they use?

Accepted Answer

Semantic segmentation. Semantic segmentation is the correct choice because it classifies every pixel in an image into a predefined category, such as road, pedestrian, vehicle, traffic sign, or sky. This pixel-level classification is essential for autonomous driving to understand the road scene at a granular level, enabling precise boundary detection and scene understanding.

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Image classification

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Object detection

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Optical character recognition (OCR)

Question 9

A retail company wants to use security cameras to analyze customer flow. They need to detect when a person enters a specific store zone, count how many people are in that zone at any given time, and track the direction each person moves within the zone. Which Azure Computer Vision capability should they use?

Accepted Answer

Spatial Analysis. Spatial Analysis is the correct Azure Computer Vision capability because it is specifically designed to analyze video feeds from cameras to detect people, count them in defined zones, and track their movement direction. Unlike general object detection, Spatial Analysis provides the specialized functions for zone occupancy and person trajectory tracking required by the retail scenario.

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Object detection

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Optical Character Recognition (OCR)

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Semantic segmentation

Question 10

A historical society has scanned hundreds of books printed in the 19th century. They want to convert the scanned images into searchable, editable text. Which Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Optical Character Recognition (OCR) is the Azure Computer Vision capability designed to extract printed or handwritten text from images and convert it into machine-readable, searchable, and editable text. For the historical society's scanned books, OCR can detect characters and words from the 19th-century prints and output them as digital text, enabling full-text search and editing.

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Object detection

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Image classification

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Facial detection

Question 11

A quality control team uses computer vision to inspect manufactured parts. They need to detect whether a part has any defects and also identify the type of defect (e.g., scratch, crack, dent) from an image. Which Azure Computer Vision capability should they use?

Accepted Answer

B: Object detection. Object detection is the correct capability because it not only identifies the presence of defects in an image but also localizes each defect with a bounding box and classifies it into specific types (e.g., scratch, crack, dent). This meets both requirements: detecting whether a part has defects and identifying the type of each defect.

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A: Image classification

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C: Semantic segmentation

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D: Optical character recognition (OCR)

Question 12

A logistics company uses security cameras to monitor boxes on warehouse shelves. They need an AI solution that can count the number of boxes on each shelf and also identify if any box is red (indicating a priority shipment). Which Azure Computer Vision capability should they use?

Accepted Answer

Image Analysis (object detection). Option A is correct because Image Analysis with object detection can identify and localize multiple objects (boxes) within an image, count them, and detect specific attributes like color (red boxes) by analyzing pixel values in the detected bounding boxes. This directly meets the requirement to count boxes and identify priority shipments based on color.

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Optical Character Recognition (OCR)

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Face detection

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Spatial analysis

Question 13

A retail company uses security cameras to monitor shelves. They want to identify whether a customer is holding a specific product (e.g., a green detergent bottle) and also determine the location of that product within the camera frame. Which Azure Computer Vision capability should they use?

Accepted Answer

Object detection. Object detection is the correct capability because it not only identifies the presence of a specific product (like a green detergent bottle) in an image but also returns bounding box coordinates that indicate the product's location within the camera frame. This dual output—classification plus localization—directly matches the requirement to both recognize the object and determine its position.

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Image classification

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Optical character recognition (OCR)

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Semantic segmentation

Question 14

A social media platform wants to automatically generate alternative text descriptions for images posted by users to improve accessibility for visually impaired users. Which Azure Computer Vision capability should be used?

Accepted Answer

Image Captioning. Image Captioning is the correct capability because it generates human-readable descriptions of image content, which directly meets the requirement to produce alternative text for accessibility. Unlike other options, it synthesizes a complete sentence describing the scene, objects, and actions, making it ideal for screen readers.

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Optical Character Recognition (OCR)

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Object Detection

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Face Detection

Question 15

A quality inspection system uses cameras to examine metal parts for surface defects. The system must identify the exact location and shape of each scratch, dent, or crack. Which Azure Computer Vision capability is best suited for this?

Accepted Answer

Semantic Segmentation. Semantic segmentation is the correct choice because it classifies every pixel in an image, allowing the system to precisely delineate the exact location, shape, and boundaries of surface defects like scratches, dents, or cracks on metal parts. This pixel-level granularity is essential for quality inspection where the geometry of each defect must be measured and analyzed.

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Image Classification

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Object Detection

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Dense Captioning