Everything happens somewhere – applying machine learning to geospatial analysis
Join the GeoAI Challenge in 2023 (second edition), a competition aimed at providing solutions for collaboratively addressing real-world geospatial problems by applying artificial intelligence (AI)/machine learning (ML). Through this platform, participants will attempt to address the UN Sustainable Development Goals (SDGs) related problems using real-world data. In addition, participants will acquire hands-on experience in AI/ML in areas relevant to solving SDGs and compete for prizes, recognition, and certificates.
Join the GeoAI Challenge in 2023 (second edition), a competition aimed at providing solutions for collaboratively addressing real-world geospatial problems by applying artificial intelligence (AI)/machine learning (ML). Through this platform, participants will attempt to address the UN Sustainable Development Goals (SDGs) related problems using real-world data. In addition, participants will acquire hands-on experience in AI/ML in areas relevant to solving SDGs and compete for prizes, recognition, and certificates.
ITU provides a state-of-the-art, free-of-charge compute platform to participants of the Challenge who do not have adequate access to compute in their respective institutions. The compute platform will provide participants with access to:
Free GPUs and CPUs
Hosted Jupyter notebook server
Python kernel
Pre-installed machine learning packages, e.g. PyTorch and Tensorflow
In some of the problem statements, a baseline or reference solution may be offered which may include implementations using Jupyter notebooks.
The GeoAI Challenge features five problem statements
Landslide Susceptibility Mapping
Develop ML algorithms that can analyze large dataset to identify patterns indicating high probability of landslide occurrence and create a landslide susceptibility map.
Crowdsourcing multiple solutions for high-impact problems that could improve real production AI/ML systems
Increasing awareness about the problem domain and your work either in research or business
Access to a growing and highly skilled talent pool of AI researchers, students, and professionals interested in the same problems as your group for further collaborations or hiring
