Artificial intelligence oceanography / (Record no. 14167)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02503cam a2200205 i 4500 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9789811963773 |
| INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9811963754 |
| TITLE STATEMENT | |
| Title | Artificial intelligence oceanography / |
| Statement of responsibility, etc | Xiaofeng Li, Fan Wang, editors. |
| Copyright Date | |
| Place of publication | Singapore : |
| Name of publisher | Springer, |
| Year of publication or production | [2023] |
| Copyright Date | |
| Year of publication or production | ©2023 |
| PHYSICAL DESCRIPTION | |
| Number of Pages | 1 online resource (xii, 346 pages) : |
| Other physical details | illustrations (chiefly color) |
| FORMATTED CONTENTS NOTE | |
| Formatted contents note | 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. |
| SUMMARY, ETC. | |
| Summary, etc | 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. . |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Oceanography |
| SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence. |
| ADDED ENTRY--PERSONAL NAME | |
| Personal name | Li, Xiaofeng, |
| ADDED ENTRY--PERSONAL NAME | |
| Personal name | Wang, Fan, |
| ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://directory.doabooks.org/handle/20.500.12854/97808 |
| ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Books |
| Permanent Location | Current Location | Date acquired | Full call number | Accession Number | Koha item type |
|---|---|---|---|---|---|
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/07/2024 | G28.05 .A78 2021 | 0194498 | Books |
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/07/2024 | G28.05 .A78 2021 | 0194499 | Books |
| Gabriel Afolabi Ojo Central Library (Headquarters). | Gabriel Afolabi Ojo Central Library (Headquarters). | 11/07/2024 | G28.05 .A78 2021 | 0194497 | Books |