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<tt> MAES2020 workshop at ICPR2020</tt><tt><br>
</tt><tt><br>
</tt><tt> ---===== Apologies for multiple posting =====---</tt><tt><br>
</tt><tt> Please distribute this call to interested parties</tt><tt><br>
</tt><tt>_______________________________________________________________________</tt><tt><br>
</tt><tt><br>
</tt><tt> Machine Learning Advances Environmental Science
(MAES@ICPR2020)</tt><tt><br>
</tt><tt><br>
</tt><tt> workshop at the</tt><tt><br>
</tt><tt> 25th International Conference on Pattern Recognition
(ICPR2020)</tt><tt><br>
</tt><tt> Milan, Italy, January 10, 2021</tt><tt><br>
</tt><tt> >>> <a class="moz-txt-link-freetext"
href="https://sites.google.com/view/maes-icpr2020/"
moz-do-not-send="true">https://sites.google.com/view/maes-icpr2020/</a>
<<<</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> D E A D L I N E I S A P P R O A C H I N G !
! !</tt><tt><br>
</tt><tt><br>
</tt><tt> * PLEASE NOTE THAT PAPERS NOT ACCEPTED IN THE ICPR2020
GENERAL *</tt><tt><br>
</tt><tt> SESSION AND FITTING MAES TOPICS COULD BE SUBMITTED
HERE !!!</tt><tt><br>
</tt><tt><br>
</tt><tt> ----> <a class="moz-txt-link-freetext"
href="https://easychair.org/conferences/?conf=maesicpr2020"
moz-do-not-send="true">https://easychair.org/conferences/?conf=maesicpr2020</a>
<----</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> /// Submission deadline: 10 October 2020 ///</tt><tt><br>
</tt><tt><br>
</tt><tt>_______________________________________________________________________</tt><tt><br>
</tt><tt><br>
</tt><tt> === Aim & Scope ===</tt><tt><br>
</tt><tt><br>
</tt><tt>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.</tt><tt><br>
</tt><tt><br>
</tt><tt>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.</tt><tt><br>
</tt><tt><br>
</tt><tt>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.</tt><tt><br>
</tt><tt><br>
</tt><tt>Extended papers of this workshop will be published as a
special issue in the journal of Environmental Modelling and
Software, Elsevier.</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt>*** Due to the COVID situation, the workshop may be held in
a hybrid or online format. All accepted papers will be published.
***</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> === Invited Talk ===</tt><tt><br>
</tt><tt><br>
</tt><tt>"Harnessing big environmental data by machine learning",
prof. Friedrich Recknagel, School of Biological Sciences,
University of Adelaide, Australia</tt><tt><br>
</tt><tt><br>
</tt><tt>(prof. Recknagel's bio: <a class="moz-txt-link-freetext"
href="http://www.adelaide.edu.au/directory/friedrich.recknagel"
moz-do-not-send="true">http://www.adelaide.edu.au/directory/friedrich.recknagel</a>)</tt><tt><br>
</tt><tt>(talk abstract: <a class="moz-txt-link-freetext"
href="https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing"
moz-do-not-send="true">https://drive.google.com/file/d/12BFBiG4pwN-6TRKCy0OuGHOgue4YbOKJ/view?usp=sharing</a>)</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> === Important Dates ===</tt><tt><br>
</tt><tt><br>
</tt><tt>- 10 October 2020 - workshop submission deadline</tt><tt><br>
</tt><tt>- 10 November 2020 - author notification</tt><tt><br>
</tt><tt>- 15 November 2020 - camera-ready submission</tt><tt><br>
</tt><tt>- 1 December 2020 - finalized workshop program</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> === Organizers ===</tt><tt><br>
</tt><tt><br>
</tt><tt> Francesco Camastra, Universita' di Napoli Parthenope,
Italy</tt><tt><br>
</tt><tt> Friedrich Recknagel, University of Adelaide, Australia</tt><tt><br>
</tt><tt> Antonino Staiano, Universita' di Napoli Parthenope,
Italy</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt> == Publicity chair ==</tt><tt><br>
</tt><tt><br>
</tt><tt> Fabio Bellavia, Universita' di Palermo, Italy</tt><tt><br>
</tt><tt><br>
</tt><tt>_______________________________________________________________________</tt><tt><br>
</tt><tt><br>
</tt><tt> Contacts: <a class="moz-txt-link-abbreviated"
href="mailto:antonino.staiano@uniparthenope.it"
moz-do-not-send="true">antonino.staiano@uniparthenope.it</a></tt><tt><br>
</tt><tt> <a class="moz-txt-link-abbreviated"
href="mailto:francesco.camastra@uniparthenope.it"
moz-do-not-send="true">francesco.camastra@uniparthenope.it</a></tt><tt><br>
</tt><tt><br>
</tt><tt> Workshop: <a class="moz-txt-link-freetext"
href="https://sites.google.com/view/maes-icpr2020/"
moz-do-not-send="true">https://sites.google.com/view/maes-icpr2020/</a></tt><tt><br>
</tt><tt> ICPR2020: <a class="moz-txt-link-freetext"
href="https://www.micc.unifi.it/icpr2020/"
moz-do-not-send="true">https://www.micc.unifi.it/icpr2020/</a></tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt><tt><br>
</tt>
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