SSML: Semi-supervised metric learning with hard samples for hyperspectral image classification
Deep learning is widely used in hyperspectral image (HSI) classification due to its powerful learning capabilities. However, its excellent performance typically requires a large number of samples, which can be time-consuming and labor-intensive to produce. The limitation of available samples greatly...
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| Autors principals: | , , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
Elsevier
2024-12-01
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| Col·lecció: | Journal of Radiation Research and Applied Sciences |
| Matèries: | |
| Accés en línia: | http://www.sciencedirect.com/science/article/pii/S1687850724003492 |
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