[Announcements] ACM TSAS CFP - SI on Deep Learning for Spatial Algorithms and Systems

[Moustafa Youssef]

Apologies for multiple posting.

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CALL FOR PAPERS


*ACM Transactions on Spatial Algorithms and Systems*

*Special issue on Deep Learning for Spatial Algorithms and Systems*

*Special Issue Guest Editors:*

Moustafa Youssef: Alexandria University, Egypt
John Krumm: Microsoft Research, USA
Muhammad Aamir Cheema: Monash University, Australia



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*Aim and Scope *

The availability of both large-scale datasets as well as the advances in
graphical processing units (GPUs) has paved the way to the recent
breakthroughs in the deep learning field. This in turn has led to
unprecedented accuracy in various applications of machine learning such as
image recognition, natural language processing, and machine translation,
among others. Spatio-temporal data sets are naturally large due to the wide
extent in both space and time. Hence, approaches based on deep learning are
well suited to systems designed to process spatio-temporal data.

This special issue on *Deep Learning for Spatial Algorithms and Systems* will
be published in *ACM Transactions on Spatial Algorithms and Systems* (TSAS)
<https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-1d253x3180dfx0443&>.
The guest editors target covering various deep-learning algorithms and
systems applied to spatial data processing.

*Topics of interest include (but are not limited to) applications of deep
learning to:*

   - Big Spatial Data
   - Location Privacy, Data Sharing and Security
   - Mobile Systems and Vehicular Ad Hoc Networks
   - Spatio-Temporal Data Analysis
   - Spatial Data Mining and Knowledge Discovery
   - Spatial Data Quality and Uncertainty
   - Spatio-Temporal Sensor Networks
   - Spatio-Temporal Stream Processing
   - Spatio-Textual Searching
   - Location-Based Services
   - Location Tracking Algorithms
   - Traffic Telematics
   - Urban and Environmental Planning
   - Crowdsourcing Spatial Data
   - Geographic Information Retrieval
   - Connected Cars, Intelligent Transportation Systems, Smart Spaces
   - Mobile Data Analytics
   - Behavioral/Activity Sensing and Analytics
   - Location-Based Social Networks
   - Location and Trajectory Analytics
   - Innovative Applications Driven by Spatial Data

The journal welcomes original articles on any of the above topics or
closely related disciplines in the context of deep learning for spatial
algorithms and systems. TSAS will encourage original submissions that have
not been published or submitted in any form elsewhere, and submissions
which may significantly contribute to opening up new and potentially
important areas of research and development. TSAS will publish outstanding
papers that are "major value-added extensions" of papers previously
published in conferences. These extensions should contribute at least 30%
new original work. In this case, authors will need to identify in a
separate document the list of extensions over their previously published
paper. For more information, please visit https://tsas.acm.org/authors.cfm.

*Important Dates*

May 1, 2019: Deadline for submissions of full-length papers
Aug 1, 2019: Notification of initial reviews
Sep 1, 2019: Deadline for revisions
Dec 1, 2019: Notification of final reviews
Jan 1, 2020: Submission of final camera-ready manuscripts
Mar 1, 2020:  Expected publication

For further information, please contact the guest editors at
deep-learning-editors at acm.org.



-- 
Prof. Moustafa Youssef
ACM Distinguished Scientist
Founder and Director, The Wireless Research Center
Alexandria University
Alexandria
Egypt

*email*: moustafa at alexu.edu.eg
*Tel*: (+20106) 417-0777
*Web*: http://wrc-ejust.org
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