Deep Learning Network Intensification for Preventing Noisy-Labeled Samples for Remote Sensing Classification
The deep-learning-network performance depends on the accuracy of the training samples. The training samples are commonly labeled by human visual investigation or inherited from historical land-cover or land-use maps, which usually contain label noise, depending on subjective knowledge and the time o...
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| Auteurs principaux: | , , , , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
MDPI AG
2021-04-01
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| Collection: | Remote Sensing |
| Sujets: | |
| Accès en ligne: | https://www.mdpi.com/2072-4292/13/9/1689 |
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