Pseudo-class distribution guided multi-view unsupervised domain adaptation for hyperspectral image classification
Unsupervised domain adaptation (UDA) has made great progress in cross-scene hyperspectral image (HSI) classification. Existing methods focus on aligning the distribution of source domain (SD) and target domain (TD). However, they all ignore the implicit class distribution information of TD data, whi...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225000032 |
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