AI-900 Describe features of computer vision workloads on Azure Practice Test 3 — 15 Questions

Question 1

A wildlife research team uses drone imagery to monitor penguin populations in a remote area. The penguins are small, blend into the rocky background, and are often only partially visible. The team has a limited set of 500 labeled drone images showing penguins. They want to build a system that accurately detects and counts penguins. Which approach should they take using Azure AI services?

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

Accepted Answer

Train a Custom Vision object detection model using the labeled images.. The pre-built Computer Vision object detection API is optimized for common objects and may not perform well on small, camouflaged penguins in rocky terrain. Custom Vision allows the team to train a dedicated object detection model using their 500 labeled images, enabling the model to learn the specific visual features of penguins in this challenging environment. This approach is ideal for domain-specific detection tasks where off-the-shelf models lack accuracy.

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Use the pre-built Computer Vision object detection API directly.

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Use the Computer Vision Image Analysis API with the 'dense captioning' feature.

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Train a Custom Vision image classification model with the labeled images.

Question 2

A logistics company scans thousands of packages daily. They need an automated system to read handwritten shipping labels to sort packages correctly. Which Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Optical Character Recognition (OCR), because the scenario requires extracting handwritten text from images of shipping labels to automate sorting. OCR is the specific Azure Computer Vision capability designed to detect and read printed or handwritten text from images, returning machine-readable text that can be used for downstream processing.

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Image Analysis (descriptions and tags)

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Object Detection

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Face API

Question 3

A beverage company uses a camera system to inspect bottles on a conveyor belt. The system must automatically identify which bottles are defective (e.g., cracked or chipped) and which are acceptable, based on the overall appearance of each bottle. The company has thousands of labeled images of bottles (defective and non-defective). Which Azure Computer Vision service should they use to train a custom model?

Accepted Answer

Custom Vision – Image classification. The scenario requires classifying each bottle image into one of two categories (defective or acceptable) based on overall appearance. Custom Vision – Image classification is designed exactly for this: it trains a model on labeled images to predict a single label per image, making it ideal for binary or multi-class classification tasks like defect detection.

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Custom Vision – Object detection

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Optical Character Recognition (OCR)

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Face API

Question 4

A warehouse deploys cameras to automatically process incoming packages. The system must read the serial numbers printed on each package label to update inventory records. The labels often have varied fonts and sizes, and may be slightly rotated. Which Azure Computer Vision capability should be used to extract the serial numbers?

Accepted Answer

Optical Character Recognition (OCR). Optical Character Recognition (OCR) is the correct Azure Computer Vision capability because it is specifically designed to extract printed or handwritten text from images, including serial numbers with varied fonts, sizes, and rotations. Azure's OCR API (part of Computer Vision) can handle skewed or rotated text by automatically detecting and correcting orientation before recognizing characters, making it ideal for warehouse labels that are not perfectly aligned.

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Object detection

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Image classification

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Facial recognition

Question 5

A real estate agency wants to create a feature on their website that automatically crops uploaded property photos to focus on the house itself, removing excess sky, ground, or other surroundings. Which Azure Computer Vision capability should they use?

Accepted Answer

Smart cropping. Smart cropping is the correct capability because it uses AI to identify the most visually salient region of an image and automatically crops it to focus on the main subject—in this case, the house—while removing irrelevant background like sky or ground. This is distinct from generic cropping as it leverages computer vision to detect the primary object and compositionally frame it.

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OCR (Optical Character Recognition)

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Image captioning

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Object detection

Question 6

A retail company uses overhead cameras to monitor shelf inventory in a store. They want to build a system that automatically detects whether a shelf section is empty or stocked, and specifically identify product categories (e.g., 'soft drinks', 'chips', 'canned goods') and count the number of items in each category. The company has a large set of labeled images showing different shelf states. Which Azure Computer Vision service should they use to build this custom detection and counting solution?

Accepted Answer

Custom Vision object detection. Custom Vision object detection is the correct choice because it allows the company to train a model on their labeled images to detect and localize specific product categories (e.g., 'soft drinks', 'chips') and count items within each category. Unlike pre-built Computer Vision features, Custom Vision enables custom object detection with bounding boxes and classification, which directly supports the requirement for detecting shelf states and counting items per category.

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Computer Vision Image Analysis with dense captioning

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Optical Character Recognition (OCR)

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Azure Machine Learning with a pre-trained YOLO model

Question 7

An e-commerce website wants to automatically remove the background from product photos uploaded by sellers so that items appear on a consistent plain background. Which Azure Computer Vision capability should they use?

Accepted Answer

Background Removal. Background Removal is the correct capability because it is specifically designed to isolate the foreground subject from the background in an image, producing a transparent or solid-color background. This directly meets the requirement of automatically removing backgrounds from product photos to create a consistent plain background. Azure's Background Removal API uses deep learning models trained on millions of images to segment the primary object from its surroundings.

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Optical Character Recognition (OCR)

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Image Captioning

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Object Detection

Question 8

A social media platform wants to automatically review user-uploaded images to flag any that contain explicit or suggestive adult content, as well as violent imagery. Which Azure Computer Vision feature should they use?

Accepted Answer

Image Analysis - Moderate content. The 'Moderate content' feature of Azure Computer Vision is specifically designed to detect adult, suggestive, and violent content in images. It returns a binary flag and confidence scores for categories like adult, racy, and gory, making it the appropriate choice for automatically flagging explicit or violent user-uploaded images.

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Optical Character Recognition (OCR)

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Image Analysis - Tags

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Face Detection

Question 9

A logistics company receives thousands of handwritten shipping forms daily. They need an automated solution to extract the destination address, sender name, and package weight from these forms. Which Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Optical Character Recognition (OCR), because the task requires extracting text (destination address, sender name, package weight) from handwritten shipping forms. Azure's OCR API, part of Computer Vision, is specifically designed to detect and read printed and handwritten text from images, making it the appropriate capability for this document processing scenario.

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Image Analysis

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Face detection

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Custom Vision

Question 10

A construction safety team wants to automatically detect whether workers on a job site are wearing hard hats by analyzing images from surveillance cameras. They have a large set of labeled images containing workers wearing hard hats and workers without hard hats. The team needs to train a model that can identify the location of each hard hat in an image. Which Azure Computer Vision service should they use?

Accepted Answer

Custom Vision – Object Detection. Custom Vision – Object Detection is specifically designed to identify and locate multiple objects within an image by drawing bounding boxes around them. The construction safety team needs to detect the location of each hard hat, which requires object detection, not just classification. Custom Vision allows training a model with labeled images that include bounding box annotations for objects like hard hats.

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Computer Vision – Optical Character Recognition (OCR)

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Face API

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Custom Vision – Image Classification

Question 11

A museum wants to automatically generate descriptive tags for its digital art collection. They need to identify objects, themes, and artistic styles in the images without any custom training. Which Azure Computer Vision feature should they use?

Accepted Answer

Azure AI Computer Vision Image Analysis. Azure AI Computer Vision Image Analysis provides pre-built models that can automatically generate descriptive tags for images, identifying objects, themes, and artistic styles without any custom training. This feature uses a set of thousands of recognizable objects, living beings, scenery, and actions, making it ideal for the museum's requirement to tag digital art without custom model development.

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Azure AI Custom Vision

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Azure AI Face service

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Azure AI Form Recognizer

Question 12

A retail company wants to use Azure Computer Vision to automatically monitor shelf inventory. They need to detect whether items are present on a shelf and count the number of items, without needing to identify the specific product type. Which prebuilt Computer Vision capability should they use?

Accepted Answer

Object detection. Object detection (Option C) is the correct prebuilt Computer Vision capability because it can both locate items within an image using bounding boxes and count them, without requiring identification of the specific product type. This aligns directly with the requirement to detect presence and count items on a shelf, as object detection outputs the coordinates and count of detected objects, not their classification into fine-grained categories.

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Optical Character Recognition (OCR)

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Image classification

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Semantic segmentation

Question 13

A travel booking website wants to automatically identify famous landmarks (e.g., Eiffel Tower, Taj Mahal) in photos uploaded by users. They want to use a prebuilt Azure Computer Vision feature without custom training. Which capability should they use?

Accepted Answer

Domain-specific models (Landmark detection). Azure Computer Vision includes prebuilt domain-specific models for landmark detection that can identify famous landmarks like the Eiffel Tower or Taj Mahal without any custom training. This capability is specifically designed to recognize well-known structures from user-uploaded photos, making it the ideal choice for the travel booking website's requirement.

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Image classification

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Optical character recognition (OCR)

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Object detection

Question 14

A hotel booking website wants to automatically analyze guest-submitted photos of hotel rooms to verify if they contain common amenities such as a bed, a desk, and a chair. They want to use a prebuilt Azure AI service without any custom training. Which feature should they use?

Accepted Answer

Object Detection. Object Detection (prebuilt) is the correct choice because it can identify and locate multiple specific objects (bed, desk, chair) within an image by drawing bounding boxes around them. This prebuilt Azure AI Vision feature requires no custom training and directly supports detecting common amenities in hotel room photos.

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Optical Character Recognition (OCR)

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Image Analysis (prebuilt)

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Handwriting OCR

Question 15

A logistics company receives thousands of handwritten shipping labels daily. They need an automated solution to extract the destination address, sender name, and package weight from these labels. Which prebuilt Azure Computer Vision capability should they use?

Accepted Answer

Optical Character Recognition (OCR). Azure Computer Vision's Optical Character Recognition (OCR) API is specifically designed to extract printed or handwritten text from images. In this scenario, the handwritten shipping labels contain textual data (destination address, sender name, package weight), and OCR can read and digitize that text for automated processing. The other options address different visual tasks—object detection, classification, or facial recognition—none of which extract text content.

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Object detection

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Image classification

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Facial recognition