From Space to Solutions:
AI-Powered Segmentation for Remote Sensing
About
From Space to Solutions:
AI-Powered Segmentation for Remote Sensing
This workshop delves into cutting-edge advancements in AI-driven image segmentation for remote sensing, enabling participants to transform raw satellite data into actionable insights. Through a hands-on approach, Participants will gain hands-on experience in training and fine-tuning existing deep learning models using their own datasets, as well as developing custom segmentation pipelines for Earth observation.
Workshop Level: Advanced Level
Workshop Language: English
Workshop Requirement: Gmail Account
Highlights
- AI-Powered Image Segmentation:Learn how deep learning techniques are enhancing remote sensing applications.
- Annotation & Preprocessing: Prepare and annotate datasets for accurate segmentation.
- Model Implementation & Fine-Tuning: Train and optimize deep learning models with your own data.
- Custom Segmentation Pipelines: Develop workflows tailored to Earth observation tasks.
- Model Inference: Apply trained models to make predictions on new or unseen data.
- Performance Evaluation: Assess and refine segmentation outputs effectively.
- Visual Interpretation of Results: Visualize segmentation outputs for better interpretation and analysis.
- Cloud Execution: Deploy and run codes on Google Colab platform.
Why Join This Workshop?
- Gain hands-on experience with AI-powered segmentation techniques using real-world remote sensing data.
- This workshop is ideal for researchers, data scientists, and professionals looking to harness AI in the context of remote sensing applications.
- Learn to build and fine-tune existing deep learning models for land cover classification.
- Benefit from expert guidance through hands-on demonstrations and interactive sessions
Eng. Mina Al-Saad
Research Associate at MBRSC Lab
Mina Al-Saad is a Research Associate and Head of Research and Development Section (R&D) at MBRSC Lab, University of Dubai. Her research focuses on Geographic Information Systems (GIS) and remote sensing, with an emphasis on AI-driven applications, including classification, autonomous object detection, semantic segmentation, and satellite calibration and validation. Mina’s research has led to numerous publications in prestigious international conferences and journals. She earned her BSc in Laser and Optoelectronics Engineering from Al-Nahrain University, Baghdad, Iraq, in 2009, followed by an MSc in the same field from the same university in 2012.