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title: README
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# Welcome to the AI for Disaster Management (AI4DM) GitHub Organization
This is the official GitHub organization for the **Advanced Study Institute on Artificial Intelligence for Disaster Management**, a 7-day intensive course sponsored by the **NATO Science for Peace and Security (SPS) Programme** (Grant G8054).
The event will be held from **November 17-25, 2025**, at the **University of Central Florida's Institute for Simulation and Training** in Orlando, FL, USA.
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About This Organization
This space serves as the central hub for all technical materials, code, datasets, and presentations related to the Advanced Study Institute. Our goal is to provide a lasting and accessible resource for all participants, both during and after the event.
Here you will find a collection of repositories dedicated to the various sessions and hands-on labs covered in the course.
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Key Course Themes
The curriculum is structured into two main parts, with dedicated repositories for each:
* **Part 1: Automated Building Damage Identification**
* Fundamentals of Image Classification & CNNs
* Effective Training of Deep Learning Models
* Hands-on Lab: Building a Damage Classification CNN with PyTorch
* **Part 2: Automating Flood Event Detection Using Satellite Imagery**
* Machine Learning Workflows for Geospatial Data
* Utilizing Hardware-Accelerated Tools (GPUs) for Efficient Processing
* Hands-on Lab: Deploying a Deep Learning Model for Flood Detection
##
Navigating the Repositories
Each repository is named to correspond with a specific session or topic from the event programme. Inside each repository, you will find:
* Presentation slides (PDF)
* Jupyter Notebooks or Python scripts for hands-on labs
* Links to relevant datasets
* Additional learning resources and documentation
##
Event Information & Links
* **Official Event Website:** [https://sites.google.com/view/nato-sps-ai4dm](https://sites.google.com/view/nato-sps-ai4dm)
* **Contact the Organizers:** For questions about the event, please email Dr. Bulent Soykan at `Bulent.Soykan@ucf.edu`.
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*This activity is sponsored by the NATO Science for Peace and Security Programme under grant G8054.*
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