Detecting Sea Surface Slicks using Automated Machine Learning-Reference-Cited by-同舟云学术

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Detecting Sea Surface Slicks using Automated Machine Learning

Published:2023-06-05 Issue: Volume: Page:
ISSN:
Container-title:OCEANS 2023 - Limerick
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Author:

Ossenbeck Milena¹,Theodorakopoulos Daphne²,Schneemann Jörge³,Ferdinand Oliver²,Ribas-Ribas Mariana⁴

Affiliation:

1. CvO University Oldenburg,Oldenburg,Germany

2. German Research Center for Artificial Intelligence (DFKI),Marine Perception Research Department,Oldenburg,Germany

3. CvO University Oldenburg Institute of Physics,ForWind - Center for Wind Energy Research,Oldenburg,Germany

4. CvO University Oldenburg,Center for Marine Sensors Institute for Chemistry and Biology of the Marine Environment (ICBM),Wilhemshaven,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10244175/10244247/10244633.pdf?arnumber=10244633

Reference42 articles.

1. Photographic records of sea-surface microlayers as a survey of pollution daily rhythm in coastal waters

2. Scikit-learn: Machine Learning in Python;pedregosa;Journal of Machine Learning Research,2011

3. Occurrence frequencies of sea-surface slicks at long and short time-scales in relation to wind speed

4. Roughness Change Analysis of Sea Surface From Visible Images by Fractals

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