Comparing Three Machine Learning Techniques for Building Extraction from a Digital Surface Model

Comparing Three Machine Learning Techniques for Building Extraction from a Digital Surface Model

Automatic building extraction from high-resolution remotely sensed data is a major area of interest for an extensive range of fields (e.g., urban planning, environmental risk management) but challenging due to urban morphology complexity. Among the different methods proposed, the approaches based on...

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Bibliographic Details
Main Authors: Nicla Maria Notarangelo, Arianna Mazzariello, Raffaele Albano, Aurelia Sole
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Applied Sciences
Subjects:
automated building extraction
machine learning (ML)
deep learning (DL)
digital surface model (DSM)
histogram of oriented gradients (HOG)
support vector machine (SVM)
Online Access:https://www.mdpi.com/2076-3417/11/13/6072

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https://www.mdpi.com/2076-3417/11/13/6072

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