Patch-Free Bilateral Network for Hyperspectral Image Classification Using Limited Samples
Recently, data-driven methods represented by deep learning have been widely used in hyperspectral image (HSI) classification and achieved the promising success. However, using less labeled samples to obtain higher classification accuracy is still a challenging task. In this study, we propose a patch...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
| Publié: |
IEEE
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/d57a13efa2ed4762aad33712b09d495d |
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