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AI-900: Utilizing Semantic Segmentation in Aerial Image Processing for Flood Identification

Explore how aerial image processing employs semantic segmentation, distinguishing flooded areas, an essential task in modern Computer Vision applications.

Table of Contents

Question

You implement an aerial image processing application to identify the flooded areas.

What common Computer Vision task is this application using?

A. Object detection
B. Semantic segmentation
C. Image classification
D. Face detection
E. Image Analysis

Answer

B. Semantic segmentation

Explanation

When the application processes images, it uses Semantic segmentation to classify pixels that belong to the particular object (in our case, flooded areas) and highlights them.

Option A is incorrect because the Object detection model helps to identify objects and their boundaries within the image.
Options C is incorrect because the Image classification model helps to classify images based on their content.
Option D is incorrect because the Face detection is a Computer vision technique that helps detect and recognize people’s faces.
Options E is incorrect because the Image Analysis helps extract information from the images, tag them, and create a descriptive image summary.

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Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump