[DMANET] Call for Papers - ICPR2020 workshop on "Machine Learning Advances Environmental Science (MAES)"

             Call for Papers - MAES@ICPR2020

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        Please distribute this call to interested parties
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 Machine Learning Advances Environmental Science (MAES@ICPR2020)

   workshop at the
 25th International Conference on Pattern Recognition (ICPR2020)
             Milan, Italy, September 13-18, 2020

     >>> https://sites.google.com/view/maes-icpr2020/ <<<

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 === Important Dates ===

   June 15th 2020 - workshop submission deadline
   July 15th 2020 - author notification
   July 30th 2020 - camera-ready submission
 August 15th 2020 - finalized workshop program


 === Aim & Scope ===

Environmental data are growing steadily in volume, complexity and
diversity to Big Data mainly driven by advanced sensor technology.
Machine learning can offer superior techniques for unravelling
complexity, knowledge discovery and predictability of Big Data
environmental science.

The aim of the workshop is to provide a state-of-the-art survey of
environmental research topics that can benefit from Machine Learning
methods and techniques. To this purpose the workshop welcomes papers on
successful environmental applications of machine learning and pattern
recognition techniques to  diverse domains of Environmental Research,
for instance, recognition of biodiversity in thermal, photo and acoustic
images, natural hazards analysis and prediction, environmental remote
sensing, estimation of environmental risks, prediction of the
concentrations of pollutants in geographical areas, environmental
threshold analysis and predictive modelling, estimation of Genetical
Modified Organisms (GMO) effects on non-target species.

The workshop will be the place to make an analysis of the advances of
Machine Learning for the Environmental Science and should indicate the
open problems in environmental research that still have not properly
benefited from Machine Learning.

Extended papers of this workshop will be published as a special issue in
the journal of Environmental Modelling and Software, Elsevier.


 === Organizers ===

  Francesco Camastra, Universita' degli Studi di Napoli Parthenope, Italy
 Friedrich Recknagel, University of Adelaide, Australia
    Antonino Staiano, Universita' degli Studi di Napoli Parthenope, Italy

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 Contacts: antonino.staiano@uniparthenope.it
francesco.camastra@uniparthenope.it

 Workshop: https://sites.google.com/view/maes-icpr2020/
 ICPR2020: https://www.micc.unifi.it/icpr2020/


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