Oceanic eddies play an important role in global energy and material transport, and contribute greatly to nutrient and phytoplankton distribution. Deep learning is employed to identify oceanic eddies from sea surface height anomalies data. In order to...
Reconstructing the vertical structures of the ocean from sea surface information is of great importance for ocean and climate studies. In this study, an ensemble machine learning (Ens-ML) model is proposed to retrieve ocean subsurface thermal structu...
Sea surface height (SSH) derived from satellite altimetry is essential for oceanographic research and marine monitoring. Although artificial intelligence (AI) models show considerable potential in forecasting, their application in oceanography remain...
The semantic segmentation of underwater imagery is an important step in the ecological analysis of coral habitats. To date, scientists produce fine-scale area annotations manually, an exceptionally time-consuming task that could be efficiently automa...
Autonomous Underwater Vehicles (AUVs) are becoming increasingly popular for large number of civil and military applications, such as environmental monitoring, oceanography, archaeology, or mine warfare. Operational safety issue still prevents the exp...
Accurate and timely water level predictions are essential for effective shoreline and coastal ecosystem management. As sea levels rise, the frequency and severity of coastal inundation events are increasing, causing significant societal and economic...
Large language model (LLM) processing, with natural language as its core, carries out information retrieval through intelligent Q&A. It has a wide range of application scenarios and is commonly considered a kind of generative AI. However, when LL...
Climate change and rising sea levels pose significant threats to coastal regions, necessitating accurate and timely forecasts. Current methods face limitations due to their inability to fully capture nonlinear complexities, high computational costs,...