Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention

Sea Surface Temperature Prediction Using ConvLSTM-Based Model with Deformable Attention

Sea surface temperature (SST) prediction has received increasing attention in recent years due to its paramount importance in the various fields of oceanography. Existing studies have shown that neural networks are particularly effective in making accurate SST predictions by efficiently capturing sp...

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Bibliographic Details
Main Authors: Benyun Shi, Conghui Ge, Hongwang Lin, Yanpeng Xu, Qi Tan, Yue Peng, Hailun He
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Remote Sensing
Subjects:
sea surface temperature
convolutional LSTM
deformable attention
spatiotemporal predictive learning
Online Access:https://www.mdpi.com/2072-4292/16/22/4126
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