Integrating Semi-Supervised Learning with an Expert System for Vegetation Cover Classification Using Sentinel-2 and RapidEye Data
In complex classification tasks, such as the classification of heterogeneous vegetation covers, the high similarity between classes can confuse the classification algorithm when assigning the correct class labels to unlabelled samples. To overcome this problem, this study aimed to develop a classifi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/15/3605 |