Spatial-Adaptive Siamese Residual Network for Multi-/Hyperspectral Classification
Deep learning methods have been successfully applied for multispectral and hyperspectral images classification due to their ability to extract hierarchical abstract features. However, the performance of these methods relies heavily on large-scale training samples. In this paper, we propose a three-d...
Збережено в:
| Автори: | , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
MDPI AG
2020-05-01
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| Серія: | Remote Sensing |
| Предмети: | |
| Онлайн доступ: | https://www.mdpi.com/2072-4292/12/10/1640 |
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