Contrastive Learning with Image Deformation and Refined NT-Xent Loss for Urban Morphology Discovery

Contrastive Learning with Image Deformation and Refined NT-Xent Loss for Urban Morphology Discovery

The traditional paradigm for studying urban morphology involves the interpretation of Nolli maps, using methods such as morphometrics and visual neural networks. Previous studies on urban morphology discovery have always been based on raster analysis and have been limited to the central city area. R...

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Bibliographic Details
Main Authors: Chunliang Hua, Daijun Chen, Mengyuan Niu, Lizhong Gao, Junyan Yang, Qiao Wang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:ISPRS International Journal of Geo-Information
Subjects:
urban form
Nolli map
NT-Xent loss
unsupervised learning
image deformation
contrastive learning
Online Access:https://www.mdpi.com/2220-9964/14/5/196
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