SAU-Net: A Novel Network for Building Extraction From High-Resolution Remote Sensing Images by Reconstructing Fine-Grained Semantic Features

The extraction of buildings from high-resolution remote sensing imagery (HRSI) is crucial across various applications and stands as a pivotal task in the field of remote sensing. While recent methods based on convolutional neural networks exhibit superior performance in building extraction from HRSI...

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Autors principals:	Meng Chen, Ting Mao, Jianjun Wu, Ruohua Du, Bingyu Zhao, Litao Zhou
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2024-01-01
Col·lecció:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Matèries:	Building extraction fine-grained semantic features remote sensing imagery supervised attention U-Net (SAU-Net)
Accés en línia:	https://ieeexplore.ieee.org/document/10453947/
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