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Artificial Intelligence Oceanography

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Cover of 'Artificial Intelligence Oceanography'

Table of Contents

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    Book Overview
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    Chapter 1 Artificial Intelligence Foundation of Smart Ocean
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    Chapter 2 Forecasting Tropical Instability Waves Based on Artificial Intelligence
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    Chapter 3 Sea Surface Height Anomaly Prediction Based on Artificial Intelligence
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    Chapter 4 Satellite Data-Driven Internal Solitary Wave Forecast Based on Machine Learning Techniques
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    Chapter 5 AI-Based Subsurface Thermohaline Structure Retrieval from Remote Sensing Observations
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    Chapter 6 Ocean Heat Content Retrieval from Remote Sensing Data Based on Machine Learning
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    Chapter 7 Detecting Tropical Cyclogenesis Using Broad Learning System from Satellite Passive Microwave Observations
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    Chapter 8 Tropical Cyclone Monitoring Based on Geostationary Satellite Imagery
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    Chapter 9 Reconstruction of p CO $$_{2}$$ 2  Data in the Southern Ocean Based on Feedforward Neural Network
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    Chapter 10 Detection and Analysis of Mesoscale Eddies Based on Deep Learning
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    Chapter 11 Deep Convolutional Neural Networks-Based Coastal Inundation Mapping from SAR Imagery: with One Application Case for Bangladesh, a UN-defined Least Developed Country
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    Chapter 12 Sea Ice Detection from SAR Images Based on Deep Fully Convolutional Networks
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    Chapter 13 Detection and Analysis of Marine Green Algae Based on Artificial Intelligence
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    Chapter 14 Automatic Waterline Extraction of Large-Scale Tidal Flats from SAR Images Based on Deep Convolutional Neural Networks
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    Chapter 15 Extracting Ship’s Size from SAR Images by Deep Learning
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    Chapter 16 Benthic Organism Detection, Quantification and Seamount Biology Detection Based on Deep Learning
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Title
Artificial Intelligence Oceanography
Published by
Springer Nature Singapore, February 2023
DOI 10.1007/978-981-19-6375-9
ISBNs
978-9-81-196374-2, 978-9-81-196375-9
Editors

Li, Xiaofeng, Wang, Fan

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 11%
Student > Ph. D. Student 3 9%
Student > Bachelor 2 6%
Student > Master 2 6%
Other 1 3%
Other 4 11%
Unknown 19 54%
Readers by discipline Count As %
Earth and Planetary Sciences 8 23%
Agricultural and Biological Sciences 2 6%
Nursing and Health Professions 1 3%
Unspecified 1 3%
Arts and Humanities 1 3%
Other 4 11%
Unknown 18 51%