Artificial Intelligence Oceanography
portes grátis
Artificial Intelligence Oceanography
Li, Xiaofeng; Wang, Fan
Springer Verlag, Singapore
02/2023
346
Mole
Inglês
9789811963773
15 a 20 dias
610
Descrição não disponível.
Theory and technology of artificial intelligence for oceanography.- Satellite data-driven internal wave forecast model based on machine learning techniques.- Detection and analysis of marine macroalgae based on artificial intelligence.- Tropical cyclone intensity estimation from geostationary satellite imagery.- Reconstructing marine environmental data based on deep learning.- Detecting oceanic processes from space-borne sar imagery using machine learning.- Deep convolutional neural networks-based coastal inundation mapping for un-defined least developed countries: taking madagascar and mozambique as examples.- Ai- based mesoscale eddy study.- Classifying sea ice types from sar images based on deep fully convolutional networks.- Detecting ships and extracting ship's size from SAR images based on deep learning.- Quality control of ocean temperature and salinity data based on machine learning technology.- automatic extraction of internal wave signature from multiple satellite sensors based on deep convolutional neural networks.- Automatic extraction of waterlines from large-scale tidal flats on SAR images and applications based on deep convolutional neural networks.- Forecast of tropical instability waves using deep learning.- Sea surface height prediction based on artificial intelligence.
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Open Access;Deep learning;Sea surface temperature;Hurricane study;Coastal inundation mapping;Sea surface height;Wind study;Mesoscale eddy study;Ocean internal wave;Sea ice;Detection of ship
Theory and technology of artificial intelligence for oceanography.- Satellite data-driven internal wave forecast model based on machine learning techniques.- Detection and analysis of marine macroalgae based on artificial intelligence.- Tropical cyclone intensity estimation from geostationary satellite imagery.- Reconstructing marine environmental data based on deep learning.- Detecting oceanic processes from space-borne sar imagery using machine learning.- Deep convolutional neural networks-based coastal inundation mapping for un-defined least developed countries: taking madagascar and mozambique as examples.- Ai- based mesoscale eddy study.- Classifying sea ice types from sar images based on deep fully convolutional networks.- Detecting ships and extracting ship's size from SAR images based on deep learning.- Quality control of ocean temperature and salinity data based on machine learning technology.- automatic extraction of internal wave signature from multiple satellite sensors based on deep convolutional neural networks.- Automatic extraction of waterlines from large-scale tidal flats on SAR images and applications based on deep convolutional neural networks.- Forecast of tropical instability waves using deep learning.- Sea surface height prediction based on artificial intelligence.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
