Discrete variational autoencoders for synthetic nighttime visible satellite imagery
Visible satellite imagery (VIS) is essential for monitoring weather patterns and tracking ground surface changes associated with climate change. However, its availability is limited during nighttime. To address this limitation, we present a discrete variational autoencoder (VQVAE) method for transla...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Cambridge University Press
2025-01-01
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| Series: | Environmental Data Science |
| Subjects: | |
| Online Access: | https://www.cambridge.org/core/product/identifier/S2634460225100150/type/journal_article |
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