-------- Forwarded Message --------
Subject: [AISWorld] CFP_International Workshop on Artificial Intelligence for 3D Big Spatial Data Processing - AI3D2020 (CCIS)
Date: Tue, 17 Mar 2020 10:41:51 +0100
From: Hesti Sudjana <hesti.sudjana@jku.at>
To: aisworld@lists.aisnet.org


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We apologize if you receive multiple copies of this CFP
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C A L L F O R P A P E R S


The 3rd International Workshop on Artificial Intelligence for 3D Big
Spatial Data Processing - AI3D2020
September 14 - 17, 2020
Bratislava, Slovakia
http://www.dexa.org/ai3d2020
email: ai3d2020@easychair.org
Papers submission: https://easychair.org/conferences/?conf=ai3d2020


*** Authors will be allowed to present their work virtually if needed to
ensure both the safety of participants and wide dissemination of their
work. We will announce further instructions regarding this in the due
time. ***
*** IMPORTANT DATES ***
Paper submission: March 16, 2020, March 26, 2020 (EXTENDED)
Notification of acceptance: May 20, 2020
Camera-ready copies due: June 19, 2020
*** PUBLICATION ***
All accepted papers will be published by Springer in "Communications in
Computer and Information Science".

*** SCOPE ***
The AI3D 2020 workshop is intended to provide a common forum for
researchers, scientists, engineers, and practitioners throughout the
world to present their latest research findings, developments, and
applications in the area of Artificial Intelligence for 3D Big Spatial
Data Processing. Recent advances in laser technology has resulted in the
generation of a massive amount of 3D spatial data. The 3D spatial data
offer a useful source of information for natural resource management,
urban panning, autonomous driving, etc. Artificial intelligence (AI) has
the potential to take the 3D spatial data processing into hyper-growth.
Recently, 3D indoor mapping systems, terrestrial mobile mapping systems
(MMS) and airborne LiDAR systems are capable of collecting terabytes of
data (including images and point clouds) in a single scan or on a single
trip. Existing approaches and tools lack the efficient management,
processing and analysis of 3D spatial data. Many of these issues can be
solved by using Artificial Intelligence and Deep Learning to redefine the
work flow. This workshop focuses on the use of Artificial Intelligence
and Deep Learning to improve the processing, management and analysis of
3D Big Spatial data. The workshop aims at providing a platform to the
group of researchers working in this direction to share their work,
exchange ideas, and solve research problems.

*** TOPICS OF INTEREST ***
A list of topics of interest includes but is not limited to: - AI and the 3D scanning technologies and devices
- Use of AI in 3D view registration and surface modeling
- Intelligent LiDAR data processing, management and analysis
- Point cloud data processing and analysis
- 3D modeling and depth image processing
- Spatio-temporal data processing and analysis
- Geo spatial data processing and analysis
- Distributed, parallel and peer-to-peer approaches to index, search and
\item process 3D Big spatial data
- AI based object detection from point cloud and images
-Supervised/Unsupervised object annotation in 3D data
- Point cloud data indexing and querying
- 3D Big spatial data architectures
- 3D Big spatial data visualisation and analytics
- 3D Big spatial data cleaning, compression and integration
- Geographic Information Retrieval
- Indoor and outdoor mapping
- 3D mapping
- Urban Planning
- Spatial data applications
- User Interfaces and Visualization
*** SUBMISSION GUIDELINES ***
Authors are invited to electronically submit original research
contributions or experience reports in English. AI3D 2020 will accept
submissions of both short (up to 10 pages) and full papers (up to 15
papers). The submitted manuscript should closely reflect the final paper
as it will appear in the Proceedings. AI3D reserves the right to accept
papers only as shorinnovative ideas which still require further technical development. Any
submission that significantly exceeds length limits or deviates from
formatting requirements may be rejected without review. Formatting guidelines: http://www.dexa.org/formatting_guidelines
Online Papers Submission:
https://easychair.org/conferences/?conf=ai3d2020
*** REVIEW PROCESS ***
Submitted papers will be carefully evaluated based on originality,
significance, technical soundness, and clarity of exposition. Duplicate
submissions are not allowed and will be rejected immediately without
further review. Authors are expected to agree to the following terms: "I
understand that the submission must not overlap substantially with any
other paper that I am a co-author of or that is currently submitted
elsewhere. Furthermore, previously published papers with any overlap are
cited prominently in this submission." Questions about this policy or
how it applies to a specific paper should be directed to the PC
Co-chairs.

*** ACCEPTED PAPERS ***
All accepted papers will be published by Springer in "Communications in
Computer and Information Science (CCIS). Authors of all accepted papers
must sign a Springer copyright release form. Papers are accepted with
the understanding that at least one author will register for the
conference to present the paper. All published papers will be indexed
appropriately in all major indexes.
*** Organisation Committee ***
General Co-Chairs:
- Prof. Dr. Sisi Zlatanova, UNSW, Australia
- Dr. Kyoung-Sook Kim, AIRC, AIST, Japan

Program Chair:
- Dr. Salman Ahmed Shaikh, AIRC, AIST, Japan

Program committees: http://www.dexa.org/ai3d2020

Further inquiries please contact PC chairs/co-Chairs
(ai3d2020@easychair.org)

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Hesti Sudjana Departement of Telecooperation Johannes Kepler University Linz
Science Park 3, Altenberger Straße 69, 4040 Linz, Austria
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