PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification
Polarimetric synthetic aperture radar (PolSAR) has rich polarization information, offering an efficient and reliable means of collecting information. However, how to effectively leverage these complex data to extract polarization features remains a key challenge. Recently, contrastive learning has b...
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| Главные авторы: | , , , , , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
IEEE
2025-01-01
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| Серии: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Предметы: | |
| Online-ссылка: | https://ieeexplore.ieee.org/document/10948157/ |
| Метки: |
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