Connectionists: CFP - MAES at ICPR2020 workshop - INVITED TALK ANNOUNCED!

[Fabio Bellavia]

                      MAES2020 workshop at ICPR2020

            ---===== Apologies for multiple posting =====---
           Please distribute this call to interested parties
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    Machine Learning Advances Environmental Science (MAES at ICPR2020)

                            workshop at the
    25th International Conference on Pattern Recognition (ICPR2020)
                   Milan, Italy, January 10, 2021
          >>> https://sites.google.com/view/maes-icpr2020/ <<<


           S U B M I S S I O N S     A R E    O P E N   ! ! !

     * PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020 GENERAL *
       SESSION AND FITTING MAES TOPICS COULD BE SUBMITTED HERE !!!

     ----> https://easychair.org/conferences/?conf=maesicpr2020 <----


               /// Submission deadline: 10 October 2020 ///

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  === 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.


*** Due to the COVID situation, the workShop may be held in a hybrid or 
online format. All accepted papers will be published. ***


  === Invited Talk ===

"Harnessing big environmental data by machine learning", prof. Friedrich 
Recknagel, School of Biological Sciences, University of Adelaide, Australia

(prof. Recknagel's bio: 
http://www.adelaide.edu.au/directory/friedrich.recknagel)
(talk abstract: 
https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing)


  === Important Dates ===

-  10 October  2020 - workshop submission deadline
-  10 November 2020 - author notification
-  15 November 2020 - camera-ready submission
-   1 December 2020 - finalized workshop program


  === Organizers ===

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


  == Publicity chair ==

       Fabio Bellavia, Universita' di Palermo, Italy

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  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/