Builtup Area Classification using K-Means and DNN

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Builtup Area Classification using K-Means and DNN

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Abstract

This project classifies built-up areas from satellite images using K-Means clustering and a Deep Neural Network (DNN). K-Means segments the image, and DNN accurately classifies built-up and non-built-up regions. The system improves accuracy and automation in urban area detection.

Existing System

Manual and traditional classification methods
Low accuracy
Time-consuming

Proposed System

K-Means for segmentation
DNN for classification
Higher accuracy and automated detection

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Builtup Area Classification using K-Means and DNN

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