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AI-900 · Question #244

Drag and Drop Question Match the types of computer vision workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the…

The correct answer is Optical character recognition (OCR); Object detection; Image classification. The correct arrangement matches each scenario to its most appropriate computer vision workload: OCR is used when the goal is to extract and recognize text from images or documents (e.g., digitizing printed forms); Object detection identifies and locates multiple specific…

Submitted by anna_se· Mar 30, 2026Describe features of computer vision workloads on Azure (Microsoft Azure AI Fundamentals - AI-900)

Question

Drag and Drop Question Match the types of computer vision workloads to the appropriate scenarios. To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all. NOTE: Each correct selection is worth one point. Answer:

Exhibit

AI-900 question #244 exhibit

Answer Area

Drag items

Image classificationObject detectionOptical character recognition (OCR)

Correct arrangement

  • Optical character recognition (OCR)
  • Object detection
  • Image classification

Explanation

The correct arrangement matches each scenario to its most appropriate computer vision workload: OCR is used when the goal is to extract and recognize text from images or documents (e.g., digitizing printed forms); Object detection identifies and locates multiple specific objects within an image by drawing bounding boxes around them (e.g., counting cars in a parking lot); Image classification assigns a single label or category to an entire image (e.g., determining whether a photo shows a cat or a dog). Each workload type addresses a distinct level of visual analysis - from whole-image labeling, to locating instances of objects, to reading textual content.

Topics

#Computer Vision#Image Classification#Object Detection#OCR

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