New Quantitative Approach for the Morphological Similarity Analysis of Urban Fabrics Based on a Convolutional Autoencoder

New Quantitative Approach for the Morphological Similarity Analysis of Urban Fabrics Based on a Convolutional Autoencoder

Urban fabric similarity analysis and classification represent a useful analysis framework in many urban studies. Classical approaches include qualitative descriptions or manually selected indicators, depending largely on the researcher's knowledge. This paper proposes a new method for extractin...

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Bibliographic Details
Main Authors: Jia Dong, Li Li, Dongqing Han
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Urban fabric
urban morphology
deep learning
convolutional autoencoder
hierarchical cluster
Online Access:https://ieeexplore.ieee.org/document/8781683/

Internet

https://ieeexplore.ieee.org/document/8781683/

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