Xinchang Zhang1, Xiaokang Pan2, Rongjie Zhu3, Runda Guan2, Zhongfeng Qiu4, Biao Song5,*
CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1827-1846, 2024, DOI:10.32604/cmes.2024.054298
Abstract Identification of ocean eddies from a large amount of ocean data provided by satellite measurements and numerical simulations is crucial, while the academia has invented many traditional physical methods with accurate detection capability, but their detection computational efficiency is low. In recent years, with the increasing application of deep learning in ocean feature detection, many deep learning-based eddy detection models have been developed for more effective eddy detection from ocean data. But it is difficult for them to precisely fit some physical features implicit in traditional methods, leading to inaccurate identification of ocean eddies. In… More >
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