Heterogeneous Network-Based Contrastive Learning Method for PolSAR Land Cover Classification

Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classification. Supervised learning (SL) requires a large amount of labeled PolSAR data with high quality to achieve better perf...

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Dades bibliogràfiques

Autors principals:	Jianfeng Cai, Yue Ma, Zhixi Feng, Shuyuan Yang, Licheng Jiao
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2024-01-01
Col·lecció:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Matèries:	Contrastive learning (CL) feature selection few-shot learning polarimetric synthetic aperture radar (PolSAR) image classification superpixel
Accés en línia:	https://ieeexplore.ieee.org/document/10601228/
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