A high-resolution remote sensing land use/land cover classification method based on multi-level features adaptation of segment anything model

Land use/land cover (LULC) classification based on deep learning techniques is a significant research area for analyzing high-resolution remote sensing(HRRS) images. However, due to the limitation of available samples and model feature extraction capability, the current deep learning methods suffer...

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Detalhes bibliográficos

Principais autores:	Hui Yang, Zhipeng Jiang, Yaobo Zhang, Yanlan Wu, Heng Luo, Peng Zhang, Biao Wang
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Elsevier 2025-07-01
coleção:	International Journal of Applied Earth Observations and Geoinformation
Assuntos:	Land use/land cover classification Segment anything model(SAM) Parameter efficient fine-tuning High-resolution remote sensing images Semantic segmentation
Acesso em linha:	http://www.sciencedirect.com/science/article/pii/S1569843225003061
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