Crop classification in South Korea for multitemporal PlanetScope imagery using SFC-DenseNet-AM
In this manuscript, a new methodology based on a deep learning model using a Siamese network and attention module was proposed to classify crop cultivation areas, such as onion and garlic, from multitemporal PlanetScope images in South Korea. To consider the seasonal characteristics of crops in the...
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| Hauptverfasser: | , , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Elsevier
2024-02-01
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| Schriftenreihe: | International Journal of Applied Earth Observations and Geoinformation |
| Schlagworte: | |
| Online-Zugang: | http://www.sciencedirect.com/science/article/pii/S1569843223004430 |
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