[CFP - 2 weeks left until the deadline] - Workshop on Complex Data Challenges in Earth Observation @IJCAI-ECAI 2022
Aleksandra Gruca
2nd workshop on Complex Data Challenges in Earth Observation
Workshop website: 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 modelling, 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 organised 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
Invited Speakers
Nebojsa Jojic, Microsoft Research, USA
Title: Geospatial AI at Scale
Vipn Kumar, University of Minnesota, USA
Title: Big Data in Climate and Earth Sciences: Challenges and Opportunities for Machine Learning
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 dates: 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. 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 two column 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 into the workshop proceedings. 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.
https://www.iarai.ac.at/landslide4sense/
Workshop Venue
The workshop is part of IJCAI-ECAI 2022 conference. The conference venue is Messe Wien Exhibition and Congress Center, which is one of the most modern exhibition and conference centres.
Messe Wien Hall B, entrance Congress Center Messeplatz 1 A-1020 Vienna
Please find more information about the conference venue here: https://ijcai-22.org/venue/
Organising 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: cd...@iarai.ac.at