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A Review of Self-Organizing Map Applications in Meteorology and Oceanography [chapter]

Yonggang Liu, Robert H.
2011 Self Organizing Maps - Applications and Novel Algorithm Design  
The first two are for observing and modeling thee West Florida Shelf circulation. The last is for applications to harmful algae under the ECOHAB program. This is CPR contribution #10.  ...  , and long time series of numerical model outputs.  ...  Numerical ocean models also generate huge amount of "data" that need to be effectively analyzed. SOM has already found its application in describing numerical ocean model output.  ... 
doi:10.5772/13146 fatcat:lcjfgwbs3jdgfionhdz5zewj34

Biogeographic assessments: A framework for information synthesis in marine spatial planning

Chris Caldow, Mark E. Monaco, Simon J. Pittman, Matthew S. Kendall, Theresa L. Goedeke, Charles Menza, Brian P. Kinlan, Bryan M. Costa
2015 Marine Policy  
Coastal and marine spatial planning Spatial predictive modeling Human uses Ecosystem-based management Seascape ecology a b s t r a c t This paper presents the Biogeographic Assessment Framework (BAF),  ...  This paper describes the structure of the BAF framework and the associated analytical techniques.  ...  National Oceanic and Atmospheric Administration's National Centers for Coastal Ocean Science and Office of National Marine Sanctuaries. BPK, SJP and  ... 
doi:10.1016/j.marpol.2014.07.023 fatcat:vx7ctewlgvbxrjcnh3mgoxn4ae

Review on Applications of Machine Learning in Coastal and Ocean Engineering

Taeyoon Kim, Woo-Dong Lee
2022 한국해양공학회지  
Recently, an analysis method using machine learning for solving problems in coastal and ocean engineering has been highlighted.  ...  Herein, we introduce and describe the application trend of machine learning models in coastal and ocean engineering.  ...  Linear Regression (LR) Model The LR model uses linear parameters and offers easy and quick analyses.  ... 
doi:10.26748/ksoe.2022.007 fatcat:happhvmp5beozidffwt2re3quq

Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook

Morten Goodwin, Kim Tallaksen Halvorsen, Lei Jiao, Kristian Muri Knausgård, Angela Helen Martin, Marta Moyano, Rebekah A Oomen, Jeppe Have Rasmussen, Tonje Knutsen Sørdalen, Susanna Huneide Thorbjørnsen, David Demer
2022 ICES Journal of Marine Science  
We provide insight into popular DL approaches for ecological data analysis, focusing on supervised learning techniques with deep neural networks, and illustrate challenges and opportunities through established  ...  Off-the-shelf algorithms find, count, and classify species from digital images or video and detect cryptic patterns in noisy data.  ...  These techniques have won numerous pattern recognition and machine learning competitions for image and sound analytics (Schmidhuber, 2015; Tessler et al., 2017) .  ... 
doi:10.1093/icesjms/fsab255 fatcat:w7pxpzfdmvfszes66kujlmasc4

Application of deep learning techniques for determining the spatial extent and classification of seagrass beds, Trang, Thailand

Takehisa Yamakita, Fumiaki Sodeyama, Napakhwan Whanpetch, Kentaro Watanabe, Masahiro Nakaoka
2019 Botanica Marina  
Remote sensing is one of the best methods for observing these dynamic patterns, and the advent of deep learning technology has led to recent advances in this method.  ...  Automatic classification of benthic cover using deep learning provided similar or better accuracy than that of the other methods even when grayscale images were used.  ...  The transformation model was developed using automatic learning of a loss function to achieve the goal of "making the output indistinguishable from reality."  ... 
doi:10.1515/bot-2018-0017 fatcat:t7u6vlqcw5dhpiwzrumlzxdgki

Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook [article]

Morten Goodwin, Kim Tallaksen Halvorsen, Lei Jiao, Kristian Muri Knausgård, Angela Helen Martin, Marta Moyano, Rebekah A. Oomen, Jeppe Have Rasmussen, Tonje Knutsen Sørdalen, Susanna Huneide Thorbjørnsen
2021 arXiv   pre-print
We provide insight into popular deep learning approaches for ecological data analysis in plain language, focusing on the techniques of supervised learning with deep neural networks, and illustrate challenges  ...  To facilitate these collaborations and promote the use of deep learning towards ecosystem-based management of the sea, this paper aims to bridge the gap between marine ecologists and computer scientists  ...  These techniques have won numerous pattern recognition and machine learning competitions for image and sound analytics [Tessler et al., 2017 , Schmidhuber, 2015] .  ... 
arXiv:2109.14737v1 fatcat:ye4vioozefgvrhlq5zqjr6qwee

Image Classification with Convolutional Neural Networks Using Gulf of Maine Humpback Whale Catalog

Nuria Gómez Blas, Luis Fernando de Mingo López, Alberto Arteta Albert, Javier Martínez Llamas
2020 Electronics  
This paper presents a study and implementation of a convolutional neural network to identify and recognize humpback whale specimens by processing their tails patterns.  ...  While whale cataloging provides the opportunity to demonstrate the potential of bio preservation as sustainable development, it is essential to have automatic identification models.  ...  This research has no funding sponsors so they had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish  ... 
doi:10.3390/electronics9050731 fatcat:swfutodpyndhjbadgw4u6wzzp4

Deep Neural Networks for Marine Debris Detection in Sonar Images [article]

Matias Valdenegro-Toro
2019 arXiv   pre-print
Our results show that for the evaluated tasks, DNNs are a superior technique than the corresponding state of the art. There are large gains particularly for the matching and detection proposal tasks.  ...  Proper waste disposal and recycling is a must in any sustainable community, and in many coastal areas there is significant water pollution in the form of floating or submerged garbage.  ...  Other machine learning techniques perform well, but are not competitive versus a CNN, with just one exception.  ... 
arXiv:1905.05241v1 fatcat:5t5qm54zjvfdfm3yi5mdgsgbyu

Tropical cyclone track forecasting techniques ― A review

Chandan Roy, Rita Kovordányi
2012 Atmospheric research  
This new technique uses freely available satellite images as input, can be run on standard PCs, and can produce forecasts with good accuracy.  ...  performance in all ocean basins.  ...  Sub-module 2: Image segmentation using a Composite Neural Oscillatory Model (CNOM) Sub-module 3: Pattern recognition and classification using NOEGM Module 2: Tropical cyclone track and intensity forecasting  ... 
doi:10.1016/j.atmosres.2011.09.012 fatcat:pfdst3tzvbchjjiig2vb7fo5ve

The Role of Environmental Drivers in Humpback Whale Distribution, Movement and Behavior: A Review

Jan-Olaf Meynecke, Jasper de Bie, Jan-Lukas Menzel Barraqueta, Elisa Seyboth, Subhra Prakash Dey, Serena B. Lee, Saumik Samanta, Marcello Vichi, Ken Findlay, Alakendra Roychoudhury, Brendan Mackey
2021 Frontiers in Marine Science  
The existing studies of the relationship between oceanic conditions and humpback whale ecology provide the basis for understanding impacts on this species.  ...  Here we have determined the most relevant environmental drivers identified in peer-reviewed literature published over the last four decades, and assessed the methods used to identify relationships.  ...  In the second step, the selected model predicts a spatial pattern, which can include parametric models (e.g., GAMs and GLMs) or machine learning techniques (e.g., BRTs, RFs, and MAXENT).  ... 
doi:10.3389/fmars.2021.720774 fatcat:vggmch2m7zewbgq253oxl3auxu

Earth Observation and Machine Learning Reveal the Dynamics of Productive Upwelling Regimes on the Agulhas Bank

Fatma Jebri, Meric Srokosz, Zoe L. Jacobs, Francesco Nencioli, Francesco Nencioli, Ekaterina Popova
2022 Frontiers in Marine Science  
The combined application of machine learning and satellite observations offers a new way for analysing complex ocean biological and physical processes.  ...  The SOM patterns show marked year-to-year variability.  ...  The SOM technique also enabled us to determine how long the dominant variability patterns persisted in time.  ... 
doi:10.3389/fmars.2022.872515 doaj:25ceae0265154231aff34e94e636ac37 fatcat:47ihfla3kbfablea2ntnanccz4

Developing human capital for successful implementation of international marine scientific research projects

R.J. Morrison, J. Zhang, E.R. Urban, J. Hall, V. Ittekkot, B. Avril, L. Hu, G.H. Hong, S. Kidwai, C.B. Lange, V. Lobanov, J. Machiwa (+6 others)
2013 Marine Pollution Bulletin  
This paper reviews the current activities aimed at increasing marine research capacity in developing and emerging countries and analyses the challenges faced, including: appropriate alignment of the research  ...  a r t i c l e i n f o a b s t r a c t The oceans play a crucial role in the global environment and the sustainability of human populations, because of their involvement in climate regulation and provision  ...  arose from activities relating to CB for marine science supported by the Asia-Pacific Network for Global Change Research (APN) (Project Reference Number: CBA2012-06NSY_Zhang), the SCOR/IGBP-IMBER, State Oceanic  ... 
doi:10.1016/j.marpolbul.2013.09.001 pmid:24055460 fatcat:brxgu6cuvfhinpk5sugopyddca

Introduction and executive summary [chapter]

2012 OECD Investment Policy Reviews  
RS and GIS techniques were used to perform landscape scale analyses of coastal wetland health and change.  ...  Landscape Scale Analyses of Coastal Wetlands Health and Change Using Remote Sensing Techniques in a Gis Framework A number of tools are available to resource managers for developing effective ecosystem  ... 
doi:10.1787/9789264179172-3-en fatcat:f2kq76zs6zc6rjwxaoj6rblzia

Introduction and Executive Summary [chapter]

2014 Low-Energy Lunar Trajectory Design  
RS and GIS techniques were used to perform landscape scale analyses of coastal wetland health and change.  ...  Landscape Scale Analyses of Coastal Wetlands Health and Change Using Remote Sensing Techniques in a Gis Framework A number of tools are available to resource managers for developing effective ecosystem  ... 
doi:10.1002/9781118855065.ch1 fatcat:fjmfxhubnzbkpdimzdkm3xehhi

Introduction and Executive Summary [chapter]

2005 Infrastructure Risk Management Processes  
RS and GIS techniques were used to perform landscape scale analyses of coastal wetland health and change.  ...  Landscape Scale Analyses of Coastal Wetlands Health and Change Using Remote Sensing Techniques in a Gis Framework A number of tools are available to resource managers for developing effective ecosystem  ... 
doi:10.1061/9780784408155.int fatcat:7vtit5b3yrdgzmseswrxvps3wa
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