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

Question 1

An autonomous drone needs to navigate a forest by identifying individual trees, including their exact shape and boundaries, to avoid colliding with branches. The drone also needs to distinguish between trees and other objects like rocks. Which Azure Computer Vision capability is best suited for this requirement?

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

Accepted Answer

Semantic segmentation. Semantic segmentation is the correct choice because it classifies every pixel in an image, assigning each pixel to a specific class (e.g., 'tree', 'rock', 'branch'). This pixel-level precision allows the drone to identify the exact shape and boundaries of individual trees, which is essential for collision avoidance in a forest environment.

Answer

Image classification

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Object detection

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Optical character recognition (OCR)

Question 2

A museum wants to automatically generate detailed descriptions of artwork for a mobile app. For each painting, the app should produce a natural-language description that includes the dominant colors, the objects present in the scene, and whether the scene is indoor or outdoor. Which Azure Computer Vision capability is best suited for this task?

Accepted Answer

Image Analysis (Describe Image / Dense Captions). Image Analysis with the Describe Image or Dense Captions API is specifically designed to generate human-readable sentences summarizing the content of an image, including dominant colors, objects, and scene attributes like indoor/outdoor. This capability uses pre-trained deep learning models to produce natural-language descriptions, making it the ideal choice for the museum's requirement of detailed, automated artwork descriptions.

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Optical Character Recognition (OCR)

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Face API

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Object Detection

Question 3

A logistics company needs to automatically read handwritten addresses from package labels using cameras on a conveyor belt. The handwriting varies greatly in style, size, and orientation. Which Azure Computer Vision capability should they use?

Accepted Answer

OCR (Read API). The OCR (Read API) is specifically designed to extract text from images, including handwritten text, and is optimized for varied styles, sizes, and orientations. Unlike standard OCR, the Read API uses deep-learning models to handle unstructured documents and real-world scenarios like package labels on a conveyor belt.

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Image Analysis (describing the image content)

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Face API

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Custom Vision

Question 4

A parking lot management company uses security cameras to monitor vehicles. They need to both detect the presence of license plates in an image and read the alphanumeric characters on those plates. Which Azure Computer Vision capability should they use to achieve both requirements?

Accepted Answer

Optical Character Recognition (OCR) - Read API. (OCR - Read API) is correct because Azure's Read API is specifically designed to both detect the presence of text (including license plates) in an image and extract the alphanumeric characters from that text. This meets both requirements—detecting the plate and reading its characters—in a single call, using deep-learning-based recognition models optimized for printed and handwritten text.

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Image Analysis (describe image and detect objects)

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Face API

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Custom Vision (object detection)

Question 5

A manufacturing company uses cameras on an assembly line to inspect products for defects such as scratches, dents, and discoloration. They need to identify the specific type of defect and its location on each product. 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 defects (like scratches, dents, or discoloration) but also localizes each defect by drawing bounding boxes around them. This meets the requirement to both classify the specific defect type and report its location on the product.

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Image classification

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Semantic segmentation

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Optical character recognition

Question 6

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). 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 7

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). (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 8

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 9

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 10

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.

Answer

Image Classification

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Optical Character Recognition (OCR)

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Object Detection

Question 11

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 12

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.

Answer

Image classification

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Object detection

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Optical character recognition (OCR)

Question 13

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 14

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 15

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.

Answer

A: Image classification

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C: Semantic segmentation

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D: Optical character recognition (OCR)