978-981-19-6375-9.pdf

978-981-19-6375-9.pdf

This 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 nu...

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Γλώσσα:English
Έκδοση: Springer Nature 2023
Διαθέσιμο Online:https://link.springer.com/978-981-19-6375-9
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spelling oapen-20.500.12657-613272024-03-27T14:14:29Z Artificial Intelligence Oceanography Li, Xiaofeng Wang, Fan 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 thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences::RBK Hydrology and the hydrosphere::RBKC Oceanography (seas and oceans) thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RB Earth sciences thema EDItEUR::U Computing and Information Technology::UB Information technology: general topics thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RG Geography thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence thema EDItEUR::R Earth Sciences, Geography, Environment, Planning::RN The environment::RNU Sustainability This 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. 2023-02-13T17:28:24Z 2023-02-13T17:28:24Z 2023 book ONIX_20230213_9789811963759_62 9789811963759 https://library.oapen.org/handle/20.500.12657/61327 eng application/pdf n/a 978-981-19-6375-9.pdf https://link.springer.com/978-981-19-6375-9 Springer Nature Springer Nature Singapore 10.1007/978-981-19-6375-9 10.1007/978-981-19-6375-9 6c6992af-b843-4f46-859c-f6e9998e40d5 1220cbe3-ca3a-4650-9c38-153380312b32 9789811963759 Springer Nature Singapore 346 Singapore [...] Institute of Oceanology, Chinese Academy of Sciences IOCAS, CAS open access
institution OAPEN
collection DSpace
language English
description This 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.
title 978-981-19-6375-9.pdf
spellingShingle 978-981-19-6375-9.pdf
title_short 978-981-19-6375-9.pdf
title_full 978-981-19-6375-9.pdf
title_fullStr 978-981-19-6375-9.pdf
title_full_unstemmed 978-981-19-6375-9.pdf
title_sort 978-981-19-6375-9.pdf
publisher Springer Nature
publishDate 2023
url https://link.springer.com/978-981-19-6375-9
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