Label-Efficient Fine-Tuning for Remote Sensing Imagery Segmentation with Diffusion Models

Label-Efficient Fine-Tuning for Remote Sensing Imagery Segmentation with Diffusion Models

High-resolution remote sensing imagery plays an essential role in urban management and environmental monitoring, providing detailed insights for applications ranging from land cover mapping to disaster response. Semantic segmentation methods are among the most effective techniques for comprehensive...

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Bibliographic Details
Main Authors:	Yiyun Luo, Jinnian Wang, Jean Sequeira, Xiankun Yang, Dakang Wang, Jiabin Liu, Grekou Yao, Sébastien Mavromatis
Format:	Article
Language:	English
Published:	MDPI AG 2025-07-01
Series:	Remote Sensing
Subjects:	remote sensing imagery segmentation fine-tuning denoising diffusion probabilistic model self-supervised learning
Online Access:	https://www.mdpi.com/2072-4292/17/15/2579
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