Artificial Intelligence Oceanography
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...
Furkejuvvon:
| Eará dahkkit: | , |
|---|---|
| Materiálatiipa: | Elektrovnnalaš Girjji oassi |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
Singapore
Springer Nature
2023
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| Fáttát: | |
| Liŋkkat: | OAPEN Library: download the publication OAPEN Library: description of the publication |
| Fáddágilkorat: |
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MARC
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| 100 | 1 | |a Li, Xiaofeng |4 edt | |
| 700 | 1 | |a Wang, Fan |4 edt | |
| 700 | 1 | |a Li, Xiaofeng |4 oth | |
| 700 | 1 | |a Wang, Fan |4 oth | |
| 245 | 1 | 0 | |a Artificial Intelligence Oceanography |
| 260 | |a Singapore |b Springer Nature |c 2023 | ||
| 300 | |a 1 electronic resource (346 p.) | ||
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| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 536 | |a Institute of Oceanology, Chinese Academy of Sciences | ||
| 540 | |a Creative Commons |f by-nc-nd/4.0/ |2 cc |4 http://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 650 | 7 | |a Oceanography (seas) |2 bicssc | |
| 650 | 7 | |a Earth sciences |2 bicssc | |
| 650 | 7 | |a Information technology: general issues |2 bicssc | |
| 650 | 7 | |a Geography |2 bicssc | |
| 650 | 7 | |a Artificial intelligence |2 bicssc | |
| 650 | 7 | |a Sustainability |2 bicssc | |
| 653 | |a Deep learning | ||
| 653 | |a Sea surface temperature | ||
| 653 | |a Hurricane study | ||
| 653 | |a Coastal inundation mapping | ||
| 653 | |a Sea surface height | ||
| 653 | |a Wind study | ||
| 653 | |a Mesoscale eddy study | ||
| 653 | |a Ocean internal wave | ||
| 653 | |a Sea ice | ||
| 653 | |a Detection of ship | ||
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| 856 | 4 | 0 | |a www.oapen.org |u https://library.oapen.org/handle/20.500.12657/61327 |7 0 |z OAPEN Library: description of the publication |