Sea surface temperature reconstruction based on deep learning and its application on the spatiotemporal analysis of SST variation in the South China Sea
- “The latest research utilizes the I-DINCAE model and DNN technology to successfully reconstruct sea surface temperature data in the South China Sea, revealing its spatiotemporal variation characteristics and providing new algorithms for ocean research.”
- Vol. 29, Issue 7, Pages: 2382-2398(2025)
Received:07 November 2024,
Published:07 July 2025
DOI: 10.11834/jrs.20254493
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