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Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets (2024)
Journal Article
Gao, H., Huang, B., Chen, G., Xia, L., & Radenkovic, M. (2024). Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets. Remote Sensing of Environment, 315, Article 114425. https://doi.org/10.1016/j.rse.2024.114425

The world’s first scientific satellite for sustainable development goals (SDGSAT-1) provides valuable data about offshore small-scale ocean phenomena, including the Kármán vortex street phenomenon. Although the simulation of the oce... Read More about Deep learning solver unites SDGSAT-1 observations and Navier–Stokes theory for oceanic vortex streets.

Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima (2024)
Journal Article
Yu, Y., Huang, B., Radenkovic, M., Wang, T., & Chen, G. (2024). Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima. IEEE Transactions on Geoscience and Remote Sensing, 1-1. https://doi.org/10.1109/tgrs.2024.3464850

Subsurface chlorophyll maximum (SCM) is a crucial ecological indicator for marine ecosystems. Previous studies have indicated that this phenomenon is globally widespread. Although the biogeochemical argo assimilation results have yielded positive res... Read More about Intelligent Sparse2Dense Profile Reconstruction for Predicting Global Subsurface Chlorophyll Maxima.

ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection (2024)
Journal Article
Geng, J., Gao, H., Huang, B., Radenkovic, M., & Chen, G. (2024). ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 17, 11997-12007. https://doi.org/10.1109/jstars.2024.3419175

Ocean eddies have a significant impact on marine ecosystems and the climate because they transport essential substances in the ocean. Detection of ocean eddies has become one of the most active topics in physical ocean research. In recent years, rese... Read More about ARU2-Net: A Deep Learning Approach for Global-Scale Oceanic Eddy Detection.

Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network (2024)
Journal Article
Zhang, X., Huang, B., Chen, G., Ge, L., Radenkovic, M., & Hou, G. (2024). Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 4205214. https://doi.org/10.1109/tgrs.2024.3388040

Efficient eddy trajectory prediction driven by multiinformation fusion can facilitate the scientific research of oceanography, while the complicated dynamics mechanism makes this issue challenging. Benefiting from ocean observing technology, the eddy... Read More about Global oceanic mesoscale eddies trajectories prediction with knowledge-fused neural network.