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March 3, 2026
STIMI: A masked image modeling framework for spatiotemporal wind speed reconstruction
KQ
Kai Qu
SX
S. S. Xue
Xi'an Jiaotong University
XZ
Xiaodong Zheng
Newcastle University
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Wind speed reconstruction shows improved accuracy using the masked image modeling framework.
Key evidence includes results reflecting a significant enhancement in spatial and temporal resolution.
The approach involves spatiotemporal analysis using advanced image modeling techniques.
Results highlight the potential for improved forecasting in wind energy applications, suggesting further development.
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Qu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a7602cc6e9836116a2caa1
https://doi.org/https://doi.org/10.1016/j.neucom.2026.132945
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STIMI: A masked image modeling framework for spatiotemporal wind speed reconstruction | Synapse