[visionlist] CFP - MAES at ICPR2020 workshop - INVITED TALK ANNOUNCED!
fabio.bellavia at unifi.it
Tue Sep 1 04:27:59 -04 2020
MAES2020 workshop 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, 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 ///
=== 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
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:
=== 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
Contacts: antonino.staiano at uniparthenope.it
francesco.camastra at uniparthenope.it
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