Connectionists: [Conferences] CDCEO 2022 @ IJCAI-ECAI - 2nd Call for Papers

[Naoto Yokoya]

Apologies for cross-posting
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CALL FOR PARTICIPANTS & PAPERS



*2nd workshop on Complex Data Challenges in Earth Observation (CDCEO)in
conjunction with IJCAI-ECAI 2022, July 23-29, 2022Vienna, Austria*

Website: http://www.iarai.ac.at/cdceo22

*About CDCEO*
The Big Data accumulating from remote sensing technology in-ground, aerial,
and satellite-based Earth Observation (EO) has radically changed how we
monitor the state of our planet. The ever-growing availability of
high-resolution remote sensing data increasingly confronts researchers with
the unique machine learning challenges posed by characteristic
heterogeneity and correlation structures in these data.

In this workshop, we will bring together leading researchers from both
academia and industry across diverse domains of AI, including experts from
AI, big data, remote sensing, computer vision, spatio-temporal data
processing, geographic information systems, and weather and climate
modeling, as well as other scientists or engineers with a general interest
in the application of modern data analysis methods within the EO domain.

This workshop is organized as a physical meeting and is part of IJCAI-ECAI
2022, the 31st International Joint Conference on Artificial Intelligence,
and the 25th European Conference on Artificial Intelligence.

*Workshop Topics*
The workshop invites advanced applications and method development in image
and signal processing, data fusion, feature extraction, meta-learning, and
many more. The topics covered by the workshop theme include but are not
limited to:
- Trustworthy AI for Earth observation
- Physics-informed machine learning for Earth observation
- Human-in-the-loop Earth observation data analysis
- Edge AI for Earth observation
- Vision and language for Earth observation
- Fairness and accountability in Earth observation data analysis
- Spatio-temporal data processing and analysis
- Multi-resolution, multi-temporal, multi-sensor, and multi-modal Earth
observation data fusion
- Machine learning for weather and climate research
- Deep learning and its applications to, e.g., semantic segmentation, scene
classification, and feature extraction
- Meta learning, including transfer learning, few-shot learning, and active
learning
- Integration and aggregation of complementary remote sensing measurements
- Benchmark datasets with applications to Earth Observation

*Important Dates*
Submission starts: April 1st, 2022
Workshop paper submission deadline: May 31st, 2022
Notification of paper acceptance: June 15th, 2022
Camera-ready paper submission deadline: June 30th, 2022
Workshop date: July 23-25th, 2022 (exact date TBD)

*Submission Information*
Authors are invited to submit original papers presenting research, position
papers, or papers presenting research in progress that have not been
previously published, and are not being considered for publication
elsewhere. A blind reviewing process performed by members of the Program
Committee will be applied to select papers based on their novelty,
technical quality, potential impact, clarity, and reproducibility.

Workshop papers will be included in a Workshop Proceedings published by
http://ceur-ws.org/. Papers must be formatted in CEUR style guidelines. The
page limit is 4 – 6 pages plus references.

At least one of the authors of the accepted papers must register for the
workshop for the paper to be included in the workshop proceedings. A link
to the submission site will be provided later.

*Landslide4Sense Competition*
A special session of the workshop will present the winning solutions and
highlights from a unique Landslide4Sense competition.

Realistic data for training and testing machine learning models has become
vitally important for many branches of cutting-edge research in EO. The aim
of Landslide4Sense is to promote innovative algorithms for automatic
landslide detection using globally distributed remotely sensed images, as
well as to provide objective and fair comparisons among different methods.
discloses a unique large-scale multi-modal globally distributed benchmark
dataset consisting of satellite images with more than 5000 patches on
landslide detection.

The first three participants with the highest F1 scores will be introduced
as winners. In addition, allowing competition participants to provide
innovative ideas more freely without being limited to a clear numerical
metric, two more selected submissions will be awarded the special prizes.
The ranking of these two submissions is based on the evaluation of the
methodological descriptions of the introduced method by the Landslide4Sense
competition committee as well as international expert reviewers.

Please check our workshop website for the link to the competition website
where you can find more information on the dataset and the competition
deadlines.

*Workshop Venue*
The workshop is a part of the IJCAI-ECAI 2022 conference. The conference
venue is Messe Wien Exhibition and Congress Center, which is one of the
most modern exhibitions and conference centers.
Messe Wien
Hall B, entrance Congress Center
Messeplatz 1
A-1020 Vienna
Metro stop U2 “Messe Prater”

Please find more information about the conference venue here:
https://ijcai-22.org/venue/

*Organizing Committee*
- Pedram Ghamisi, Helmholtz-Zentrum Dresden-Rossendorf, Germany and
Institute of Advanced Research in Artificial Intelligence, Austria
- Aleksandra Gruca, Silesian University of Technology, Poland
- Naoto Yokoya, University of Tokyo, Japan; RIKEN Center for Advanced
Intelligence Project, Japan
- Jun Zhou, Griffith University, Australia
- Caleb Robinson, Microsoft AI for Good Research Lab, Redmond, USA
- Fabio Pacifici, Maxar Technologies
- Pierre-Philippe Mathieu, European Space Agency Φ-lab, Italy
- Sepp Hochreiter, Institute of Advanced Research in Artificial
Intelligence, Austria

*Contact*
cdceo at iarai.ac.at
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