Self-Supervised Learning with Trilateral Redundancy Reduction for Urban Functional Zone Identification Using Street-View Imagery

In recent years, the use of street-view images for urban analysis has received much attention. Despite the abundance of raw data, existing supervised learning methods heavily rely on large-scale and high-quality labels. Faced with the challenge of label scarcity in urban scene classification tasks,...

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Autori principali:	Kun Zhao, Juan Li, Shuai Xie, Lijian Zhou, Wenbin He, Xiaolin Chen
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2025-02-01
Serie:	Sensors
Soggetti:	street-view imagery self-supervised learning redundancy reduction urban scene classification urban functional zone identification
Accesso online:	https://www.mdpi.com/1424-8220/25/5/1504
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