Multimodal learning–based reconstruction of high-resolution spatial wind speed fields
Wind speed at the sea surface is a key quantity for a variety of scientific applications and human activities. For its importance, many observation techniques exist, ranging from in situ to satellite observations. However, none of such techniques can capture the spatiotemporal variability of the phe...
Saved in:
Main Authors: | Matteo Zambra, Nicolas Farrugia, Dorian Cazau, Alexandre Gensse, Ronan Fablet |
---|---|
Format: | Article |
Language: | English |
Published: |
Cambridge University Press
2025-01-01
|
Series: | Environmental Data Science |
Subjects: | |
Online Access: | https://www.cambridge.org/core/product/identifier/S2634460224000347/type/journal_article |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multimodal Adaptation, Reconstruction, and Deviation of Immortal Ones
by: Xinzuo Li
Published: (2024-12-01) -
Object detection and multimodal learning for product recommendations
by: Karolina Selwon, et al.
Published: (2025-01-01) -
NeuTox 2.0: A hybrid deep learning architecture for screening potential neurotoxicity of chemicals based on multimodal feature fusion
by: Xudi Pang, et al.
Published: (2025-01-01) -
DIGITALIZATION: IMPROVING THE LITERACY OF FOREIGN LANGUAGE LEARNERS THROUGH MULTIMODAL TEXTS
by: Lilis Afifah, et al.
Published: (2023-05-01) -
Enhancing foundation models for scientific discovery via multimodal knowledge graph representations
by: Vanessa Lopez, et al.
Published: (2025-01-01)