| 000 | 02503cam a2200205 i 4500 | ||
|---|---|---|---|
| 020 | _a9789811963773 | ||
| 020 | _a9811963754 | ||
| 245 | 0 | 0 |
_aArtificial intelligence oceanography / _cXiaofeng Li, Fan Wang, editors. |
| 264 | 1 |
_aSingapore : _bSpringer, _c[2023] |
|
| 264 | 4 | _c©2023 | |
| 300 |
_a1 online resource (xii, 346 pages) : _billustrations (chiefly color) |
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| 505 | 0 | _aTheory 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. | |
| 520 | _aThis open access book invites readers to learn how to develop artificial intelligence (AI)-based algorithms to perform their research in oceanography. Various examples are exhibited to guide details of how to feed the big ocean data into the AI models to analyze and achieve optimized results. The number of scholars engaged in AI oceanography research will increase exponentially in the next decade. Therefore, this book will serve as a benchmark providing insights for scholars and graduate students interested in oceanography, computer science, and remote sensing. . | ||
| 650 | 0 | _aOceanography | |
| 650 | 0 | _aArtificial intelligence. | |
| 700 | 1 | _aLi, Xiaofeng, | |
| 700 | 1 | _aWang, Fan, | |
| 856 | 4 | 0 | _uhttps://directory.doabooks.org/handle/20.500.12854/97808 |
| 942 |
_2lcc _cBK |
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| 999 |
_c14167 _d14167 |
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