You need to analyze images of vehicles on a highway and measure the distance between the vehicles. Which type of computer vision model should you use?

The correct answer is A. object detection. Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can

Submitted by neha2k· Mar 30, 2026Describe features of computer vision workloads

Question

You need to analyze images of vehicles on a highway and measure the distance between the vehicles. Which type of computer vision model should you use?

Options

Aobject detection
Bimage classification
Cfacial recognition
Doptical character recognition (OCR)

How the community answered

(19 responses)

A
79% (15)
B
11% (2)
C
5% (1)
D
5% (1)

Explanation

Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image. The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like "indoor", which can't be localized with bounding boxes. https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-

Topics

#computer vision#object detection#image analysis

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