Dimension reduction aided hyperspectral image classification with a small-sized training dataset: experimental comparisons
Hyperspectral images (HSI) provide rich information which may not be captured by other sensing technologies and therefore gradually find a wide range of applications. However, they also generate a large amount of irrelevant or redundant data for a specific task. This causes a number of issues includ...
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| Main Authors: | , , , , |
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| Format: | Default Article |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/27768 |
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