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

Fabio Bellavia fabio.bellavia at unifi.it
Mon Feb 24 14:36:38 -04 2020

              Call for Papers - MAES at ICPR2020

         ---===== Apologies for multiple posting =====---
         Please distribute this call to interested parties

  Machine Learning Advances Environmental Science (MAES at ICPR2020)

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

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


  === 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


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

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

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