A Semi-Supervised Transformer with a Curriculum Training Pipeline for Remote Sensing Image Semantic Segmentation

Semantic segmentation of remote sensing images is crucial for geospatial applications but is severely hampered by the prohibitive cost of pixel-level annotations. Although semi-supervised learning (SSL) offers a solution by leveraging unlabeled data, its application to Vision Transformers (ViTs) oft...

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Detalhes bibliográficos

Principais autores:	Peizhuo Liu, Hongbo Zhu, Xiaofei Mi, Yuke Meng, Huijie Zhao, Xingfa Gu
Formato:	Artigo
Idioma:	Inglês
Publicado em:	MDPI AG 2026-02-01
coleção:	Remote Sensing
Assuntos:	remote sensing image segmentation semi-supervised learning vision transformer curriculum learning domain adaptation data augmentation
Acesso em linha:	https://www.mdpi.com/2072-4292/18/3/480
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